Data Books

Providing an understanding of what it takes to develop, implement and run a digital strategy, this book will help you find a digital process strategy and methodology that works for your organization.

By Arve Peder Øverland

Using data from a five-year study to illustrate important concepts and scenarios along the way, this insightful book helps eliminate paralysis-by-analysis and optimize decision making for marketing performance.

By John F. Tanner Jr

Including numerous case studies on risk management, fraud detection, customer relationship management, and web analytics, this essential book reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities.

By Bart Baesens

A unique and to the-point guide to learning and using the essentials of HBase, this book discusses the fundamental foundations and concepts and covers the HBase data model, architecture, schema design, API, and administration.

By Deepak Vohra

Offering a thorough view of key knowledge and detailed insight, this all-embracing guide provides comprehensive answers and extensive details and references for everything you want to know about Apache Hive.

By Jacqueline Douglas

Providing users with state-of-the-art concepts, methods, and technologies for Big Data analytics in the fight against terrorism and crime, this expert guide includes a series of case studies and scenarios to demonstrate the application of Big Data in a national security context.

By Babak Akhgar, et al.

Applied Big Data Analytics and Its Role in COVID-19 Research introduces the most recent industrial applications and research topics on COVID-19 with big data analytics.

By Peng Zhao, Xi Chen

By combining technical details on system functionality and configuration with examples of SAP Web Reports in the corporate environment, this guide explains how to develop powerful web-based reports and dashboards within the SAP BI 7.0 environment.

By Peter Jones

This title will be removed from the Skillsoft library on May 24, 2024.

By Miltiadis D. Lytras, Paraskevi Papadopoulou (eds)

Demystifying the complexities involved in SAP asset configuration, this timely book provides configuration explanations in the simplest forms possible and provides step-by-step guidance with illustrations and practical examples.

By Andrew Okungbowa

Extending the aim of internal controls from legal compliance to include efficiency and profitability and then well beyond, this book begins with the requirements for compliance, answers compliance-relevant questions in the form of an audit guide for an SAP ERP system and in the form of risks and control descriptions, and also shows how to automate the compliance management process based on SAP GRC.

By Maxim Chuprunov

Develop the curiosity, creativity and critical thinking needed to confidently interpret, analyze and communicate with data in the workplace.

By Jordan Morrow

Showing you how to use Apache Pig to develop lightweight big data applications easily and quickly, this book shows you many optimization techniques and covers every context where Pig is used in big data analytics.

By Balaswamy Vaddeman

A tutorial on the Apache Spark platform written by an expert engineer and trainer, this book will give you the fundamentals to become proficient in using Apache Spark and know when and how to apply it to your big data applications.

By Hien Luu

This book begins by explaining different ways of interacting with Apache Spark, such as Spark Concepts and Architecture, and Spark Unified Stack.

By Hien Luu

Teaching you how to analyze vast amounts of data in record time using Apache Spark with Databricks in the Cloud, this book explains how the confluence of these pivotal technologies gives you enormous power, and cheaply, when it comes to huge datasets.

By Robert Ilijason

Taking a deep dive into SAP Fiori, Fiori architecture, landscape installation, Launchpad configuration, and more, this book shows you how SAP Fiori, based on HTML5 technology, addresses the most widely and frequently used SAP transactions like purchase order approvals, sales order creation, information lookup, and self-service tasks.

By Bince Mathew

Authored by EMC Proven Professionals, Knowledge Sharing articles present ideas, expertise, unique deployments, and best practices. This article explores how Big Data and Internet of Things continue to be enhanced to adapt to data proliferation and customer needs.

By Ahmed Fahmy, Hussam Refaat, Rudaina Mawy

This book highlights research and survey articles dedicated to big data techniques for cyber-physical system (CPS), which addresses the close interactions and feedback controls between cyber components and physical components.

By Bei Yu, Shiyan Hu

Including numerous tables, illustrations, and figures, this book presents a timely overview of cutting-edge technologies for multimedia retrieval with a special emphasis on scalability.

By Benoit Huet, Edward Y. Chang, Ioannis Kompatsiaris (eds), Stefanos Vrochidis

This title will be removed from the Skillsoft library on May 24, 2024.

By Baoying Wang, Ruowang Li, William Perrizo (eds)

Exploring the unique needs of electrical utility grids, including operational technology, IT, storage, processing, and how to transform grid assets for the benefit of both the utility business and energy consumers, this book not only provides specific examples that illustrate how analytics work and how they are best applied, but also describes how to avoid potential problems and pitfalls.

By Carol L. Stimmel

Including examples drawn from social media sources such as Twitter (tweets) and Foursquare (check-ins), this practical, hands-on guide shows how to process and derive business value from big data in real time.

By Peter Zadrozny, Raghu Kodali

Helping you become a much sought-after Spark expert, this step-by-step guide shows you how to use Spark for different types of big data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning.

By Mohammed Guller

Comparing and contrasting the different types of analysis commonly conducted with big data, this accessible reference presents clear-cut explanations of the general workings of big data tools.

By Kim H. Pries, Robert Dunnigan

Focusing on the business and financial value of big data analytics, this breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material.

By Frank Ohlhorst

Packed with case studies and the insights from some of the leading experts and organizations worldwide, this book shows you how to go from being data-rich to insight-rich, improving your decision making and creating competitive advantage.

By Jay Liebowitz (ed)

Whether you are a beginner or have some experience with big data. This book is for aspiring big data professionals, including data analysts, software developers, IT professionals, and students in computer science and related fields.

By Mayank Bhushan

Containing the latest trends in big data and Hadoop, this learn-by-doing resource explains how big Big Data is and why everybody is trying to implement it into their IT projects.

By Mayank Bhushan

Using non-technical language, this book is accessible to health care professionals who might not have an IT and analytics background. It includes case studies that illustrate the business processes underlying the use of big data and health analytics to improve health care delivery.

By Harold Lehmann, Katherine Marconi (eds)

Examining cloud computing, machine learning, and knowledge sharing, this book provides innovative insights into the influence of big data analytics and artificial intelligence and the tools, methods, and techniques for knowledge-sharing processes in virtual organizations.

By Albert Gyamfi, Idongesit Williams

Combining practical advice with technical considerations, this book provides guidance in designing an information architecture to accommodate increasingly large amounts of data, from traditional sources as well as novel sources such everyday objects that are fast becoming wired into global Internet.

By Art Licht, Louis Nagode, Robert Stackowiak, Venu Mantha

Dealing with the various mission critical problems encountered by solution architects, consultants, and software architects, this book presents patterns which provide the strong architectural foundation required to launch your next big data application.

By Himanshu Shah, Nitin Sawant

Whether you're a Fortune 500 executive or the proprietor of a restaurant or web design studio, this straightforward resource explains what big data is and how you can use it in your company to become one of tomorrow's market leaders.

By David Feinleib

Providing a plain-English explanation of what big data is (and isn't), this friendly guide discusses the technology and database options supporting it, analytics that help you get meaning from your data, how to manage it, and what it can do for your company.

By Alan Nugent, Fern Halper, Judith Hurwitz, Marcia Kaufman

A power-packed guide with solutions to crack a Big data Hadoop interview, this book covers many interview questions and the best possible ways to answer them, and provides real-world examples that will help you understand the concepts of Big Data.

By Vishwanathan Narayanan

Presenting a deep insight into the realm of big data as well as the methodology, technical architecture, analytics techniques and best practices, this handbook describes the complementary nature of traditional data warehouses and big-data analytics platforms and how they feed each other.

By Harsha Srivatsa, Madhu Jagadeesh, Soumendra Mohanty

A unique and in-depth insight into how specific companies use big data, this book profiles what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario.

By Bernard Marr

Approaching the problem of managing massive data sets from a systems perspective, this book explains the roles for each project (like architect and tester, for example) and shows how the Hadoop toolset can be used at each system stage - and then explains, in an easily understood manner and through numerous examples, how to use each tool.

By Michael Frampton

Focusing on the analytic principles of business practice and big data, this book provides an interface between the main disciplines of engineering/technology and the organizational and administrative aspects of management.

By Benjamin Lev, Fausto Pedro García Márquez

Providing a strategic road map for executives who want to clear the chaos and start driving competitive advantage and top line growth, this book reveals how to spot patterns in your customers' behavior and offers proven ways to elevate customer experiences.

By Lisa Arthur

Based on a practical framework with supporting methodology and hands-on exercises, this book brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage.

By Bill Schmarzo

Delivering a rich understanding of climate-related big data techniques, this comprehensive book highlights how to navigate huge amount of climate data and resources available using big data applications.

By Jianping Li, Zhihua Zhang

This book offers a comprehensible overview of Big Data Preprocessing, which includes a formal description of each problem. It also focuses on the most relevant proposed solutions. This book illustrates actual implementations of algorithms that helps the reader deal with these problems.

By Diego Garcı́a-Gil, Francisco Herrera, Julián Luengo, Salvador García, Sergio Ramírez-Gallego

Authored by EMC Proven Professionals, Knowledge Sharing articles present ideas, expertise, unique deployments, and best practices. This article provides an overview of various new and upcoming alternatives to Hadoop MR.

By Ravi Sharda

Describing the emergence of big data technologies and the role of Spark in the entire big data stack, this book compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark.

By Lalit Mohan Goyal, Mamta Mittal, Raghvendra Kumar (eds), Valentina E. Balas

Presenting inside stories that demonstrate the power and potential of Big Data within the business realm, this book provides the insight executives need to incorporate Big Data into a better business strategy, improving outcomes with innovation and efficient use of technology.

By Patrick McSharry, Rob Thomas

Explaining each of the full-stack technologies and, more importantly, how to best integrate them, this book provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation.

By Isaac Ruiz, Raul Estrada

This book is the basic guide for developers, architects, engineers, and anyone who wants to start leveraging the open-source software Hadoop and Hive to build distributed, scalable concurrent big data applications.

By Nitin Kumar

Examining the responses of 418 learning and development professionals in position of managers and above from varying sectors, sizes, and locations, this report explores challenges and other considerations that learning leaders must address if they are to knowledgeably and capably manage big learning data and apply the insights it has to offer today's organizational learning functions.

By ASTD Research

By making the topic accessible through stories, metaphors, and analogies even though it's a technical subject area, this timely book looks at cutting-edge companies supporting an exciting new generation of business analytics.

By Ambiga Dhiraj, Michael Minelli, Michele Chambers

Effective management means combining data, people, and analytics to create a synergistic force for innovation and growth. If you want your company to move forward with confidence, this groundbreaking book can show you how to use what you already have and acquire what you need to succeed.

By Evan Stubbs

Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency.

By Jared Dean

Offering case studies of data practices in the sciences, the social sciences, and the humanities, this book asserts that managing data over the long term requires massive investment in knowledge infrastructures, putting the future of scholarship at stake.

By Christine L. Borgman

Filled with examples that illustrate the value of analytics throughout, this book outlines a conceptual framework for data modeling that can help you immediately improve your own analytics and decision-making processes.

By Stephan Kudyba

Explaining how the main challenges for Big Data revolve around data integration and development within companies, this book explores data development processes within a context of strong competition.

By Jean-Louis Monino, Soraya Sedkaoui

Supplying a clear understanding of the interrelationships between Big Data, the new business insights it reveals, and the laws, regulations, and contracting practices that impact the use of the insights and the data, this book will enable readers to quickly grasp the key issues and effectively implement the right solutions to collecting, licensing, handling, and using Big Data.

By James R. Kalyvas, Michael R. Overly

Discussing cases such as the Snowden affair, data security, and domestic smart devices which can be hijacked by hackers, this book explains how data is stored, analyzed, and exploited by a variety of bodies from big companies to organizations concerned with disease control.

By Dawn E. Holmes

The book examines how data scientists explore, interpret and visualize our digital traces to make sense of them, and to produce new knowledge.

By Eglantine Schmitt

This title will be removed from the Skillsoft library on May 24, 2024.

By Information Resources Management Association (IRMA)

Despite the hype around big data, there is no denying that its potential to benefit organizations, businesses and customers is enormous. This book presents articles which aim to give practical guidance for all those who want to understand big data better and learn how to make the most of it.

By BCS, The Chartered Institute for IT

This book teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data.

By James Warren, Nathan Marz

Examining Big Data management from an R&D perspective, this thorough resource covers the 3S designs-storage, sharing, and security-through detailed descriptions of Big Data concepts and implementations.

By Fei Hu

Authored by EMC Proven Professionals, Knowledge Sharing articles present ideas, expertise, unique deployments, and best practices. This article discusses the various new structures of data, the three V's that form the basis of big data, and the new dimensions that have arisen as challenges while discussing the big data.

By Anuj Mediratta

Full of practical techniques, real-world examples, and hands-on exercises, this book explores the technologies involved in Big Data, as well as how to find areas of the organization that can take full advantage of big data.

By Bill Schmarzo

Illustrated with numerous real-world examples from a cross section of companies and organizations, this practical book will give you a clear understanding, blueprint, and step-by-step approach to building your own big data strategy.

By Bernard Marr

To promote effective big data computing on smart clouds or supercomputers, this book takes a technological fusion approach by integrating big data theories with cloud design principles and supercomputing standards.

By Kai Hwang

Create a data warehouse, complete with reporting and dashboards using Google's BigQuery technology. This book takes you from the basic concepts of data warehousing through the design, build, load, and maintenance phases.

By Mark Mucchetti

Understand the fundamental factors of data storage system performance and master an essential analytical skill using block trace via applications such as MATLAB and Python tools.

By Jianjun Xu

Find the right people with the right skills. This book clarifies best practices for creating high-functioning data integration teams, enabling you to understand the skills and requirements, documents, and solutions for planning, designing, and monitoring both one-time migration and daily integration systems.

By Jarrett Goldfedder

Explaining everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer, this book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology.

By Daniel Linstedt, Michael Olschimke

Helping data managers and their organizations make the most of unstructured data with an existing data warehouse, this book provides readers with what they need to know to make sense of how Big Data fits into the world of Data Warehousing.

By Krish Krishnan

Providing an introduction to the field of applied ontology that is of particular relevance to biomedicine, this thorough book covers theoretical components of ontologies, best practices for ontology design, and examples of biomedical ontologies in use.

By Andrew D. Spear, Barry Smith, Robert Arp

This title will be removed from the Skillsoft library on May 24, 2024.

By Naeem Hashmi

Including exercises and case studies with road-tested advice, this book provides ideas for improving the business performance of one's company or business functions, and emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies.

By Steve Williams

Offering a thorough view of key knowledge and detailed insight, this guide examines commercial open-source applications; commercially supported Hadoop-related products; Cloudera products and services; the Cloudera ecosystem; Cloudera Impala; and much more.

By Patrick Foreman

Featuring detailed case examples from the financial, healthcare, and manufacturing industries, this comprehensive guide will help technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming.

By Adrian Bowles, Judith Hurwitz, Marcia Kaufman

Describing the step-by-step construction of a real-world big data stack from open source software, this book builds a data stack and recounts the process, including successes, failures, and lessons learned.

By Michael Frampton

Whether you're an entrepreneur wanting to boost your business, a jobseeker looking for that employable edge, or simply hoping to make the most of your current career, this book is here to help.

By Kirill Eremenko

For anyone who wants to understand how to implement FI/CO, this practical guide provides hands-on, step-by-step instructions and real-world examples for the most frequently used FI and CO submodules found in SAP ECC 6.0.

By John Burger, Peter Jones

Providing in-depth configuration of the Sales and Distribution (SD) module in the latest version of SAP ERP, this valuable resource presents you with step-by-step instruction, conceptual explanations, and plenty of examples.

By Ashutosh Mutsaddi, Kapil Sharma

This book will guide you through the process about what you need to know and help you perform at your highest level to achieve SAP S/4 HANA and some of the best practices available today.

By Sudipta Malakar

Using a series of case studies as examples throughout, this book describes the agility that comes from collaborative commerce, and provides key decision makers the implementation roadmap they need to build a successful business ecosystem.

By Alakh Verma, Rodney Heisterberg

Get started building custom Fiori applications for your enterprise. This book teaches you how to design, build, and deploy enterprise-ready, custom Fiori applications in SAP HANA.

By Sergio Guerrero

Teaching the statistical analysis skills needed to support business decisions, this book provides projects ranging from the most basic descriptive analytical techniques to more advanced techniques such as linear regression, forecasting, inferential statistics, and more.

By Andres Fortino

Data is constantly increasing and data analysts are in higher demand than ever. This book is an essential guide to the role of data analyst.

By Rune Rasmussen, et al.

Data and Analytics Strategy for Business outlines how to build consistent, high-quality sources of data which will create business value and explores how automation, AI and machine learning can improve performance and decision making.

By Simon Asplen-Taylor

Drawing upon years of practical experience and using numerous examples and an easy to understand framework, this timely guide defines the importance of data architecture and how it can be used effectively to harness big data within existing systems.

By Daniel Linstedt, W.H. Inmon

Learn how organizational data can be governed according to ethical principles with this practical guide.

By Daragh O Brien, Katherine O'Keefe

Offering a complete overview of the data governance lifecycle, this book provides a framework and case studies that will enable you to launch your very own successful and money saving data governance program.

By John Ladley

Based on the author's years of real-world experience designing solutions, this book covers all stages of data warehousing and the role of data mapping, and includes data mapping strategies and techniques that can be applied to business use cases.

By Qamar Shahbaz Ul Haq

Data Mesh in Action teaches you pragmatic ways to decentralize your data and organize it into an effective data mesh. You'll start by building a minimum viable data product, which you'll expand into a self-service data platform, chapter-by-chapter.

By Jacek Majchrzak, Marian Siwiak, Sven Balnojan

Providing comprehensive coverage of various aspects of data mining and warehousing concepts, this book offers examples, diagrams, and questions in a simple language, a crystal clear approach, and a straightforward comprehensible presentation.

By Akash Saxena, Khushboo Saxena, Sandeep Saxena

Presenting an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies, this book features coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling, and more.

By Galit Shmueli, Nitin R. Patel, Peter C. Bruce

The book describes the standards and technologies that aid in data management and compares them to other technology business standards. The reader receives practical guidance on how to segregate and separate data into zones, as well as how to develop a model that can aid in data evolution.

By Vinicius Aquino do Vale

Supported and explained with examples that you can replicate using open-source software, this insightful book focuses on concepts, principles and practical applications that are applicable to any industry and technology environment.

By EMC Education Services

Learn how to run successful big data projects, how to resource your teams, and how the teams should work with each other to be cost effective. This book introduces the three teams necessary for successful projects, and what each team does.

By Jesse Anderson

This book investigates and explores how, in the era of social media, human cognition, algorithmic recommendation systems, and human psychology are all working together to reinforce (and exaggerate) human bias.

By Kris Shaffer

With extensive coverage of all data warehouse issues, ranging from basic technologies to the most recent findings and systems, this book illustrates the concepts with an on-going example based on the North wind database using Microsoft Analysis Services and Pentaho Business Analytics.

By Alejandro Vaisman, Esteban Zimányi

Providing several examples from real organizations, this book is a step-by-step how-to guide for designing and building an enterprise-wide data warehouse across a biomedical or healthcare institution, using a four-iteration lifecycle and standardized design pattern.

By Richard E. Biehl

Helping you navigate through the complex layers of Big Data and data warehousing, this practical and timely book provides information on how to effectively think about using all of the technologies and architectures to design the next-generation data warehouse.

By Krish Krishnan

This book is meant for Data Engineers, Data Analysts, Data Scientists, Business intelligence professionals, and Architects who want to go to the next level of Data Engineering using the Databricks platform to construct Lakehouses.

By Dr. Alan L. Dennis

This book helps readers understand how to process large amounts of data with well-known Linux tools and database solutions, use effective techniques to collect and manage data from multiple sources, transform data into meaningful business insights, and much more.

By Yusuf Aytas

Using non-technical language, this informative book provides a strategy framework, empirical data, case studies, deep insights, and pragmatic steps for any enterprise to follow and attain market leadership in today's digital era.

By Joe Weinman

Charting the sudden and spectacular rise of Digital Humanitarians by sharing their remarkable, real-life stories, this book highlights how their humanity, coupled with innovative solutions to Big Data, is changing humanitarian response forever.

By Patrick Meier

Addressing the key aspects of distributed processing in big data analytics, this valuable book tackles the essential concepts and patterns of distributed computing widely used in big data analytics.

By Ganesh Chandra Deka (eds), Robin Singh Bhadoria, Sourav Mazumder

This book is an essential research publication that explores current innovative activities focusing on the integration between data warehousing and data mining with an emphasis on the applicability to real-world problems.

By David Taniar, Johanna Wenny Rahayu (eds)

Discover the capabilities and features of SAP Analytics Cloud to draw actionable insights from a variety of data, as well as the functionality that enables you to meet typical business challenges.

By Shreekant Shiralkar, Vinayak Gole

This title will be removed from the Skillsoft library on May 24, 2024.

By Martin Atzmueller, Samia Oussena, Thomas Roth-Berghofer (eds)

Covering best practices for managing and leading an enterprise-scale business intelligence (BI) and data warehousing (DW) program, this essential book describes what the Enterprise Program Manager must accomplish to orchestrate the many moving parts involved.

By Alan Simon

Explaining concepts in simple English with minimal use of jargon, this concise book covers each of the pillars of Enterprise Information Management (EIM) in depth, and provides readers with a comprehensive view of the building blocks for EIM.

By Saumya Chaki

This book is specifically targeted at developers who are fluent in SAP's programming language, ABAP, and are looking to learn the Java language. The author explores SAP, JavaServer Pages, JDBC, and Enterprise Java Beans.

By Austin Sincock

Providing practical tips and techniques for implementing an EIMS, strategies for exploiting distributed processing to handle big data for EIMS, and examples from real applications, this book explains big data's impact on MDM and the critical role of entity information management system (EIMS) in successful master data management (MDM).

By John R. Talburt, Yinle Zhou

Including numerous templates, detailed examples, and practical advice, this book presents a systematic, proven approach to improving data quality by combining a conceptual framework for understanding information quality with techniques and instructions.

By Danette McGilvray

Packed with real-world use cases and examples, this book teaches you to convert raw data into measurable behavior metrics, calculate customer lifetime value, and improve churn forecasting with demographic data.

By Carl Gold

The book serves as a comprehensive introduction and background to anyone who is interested in the subject in order to do further research on the individual subjects included here.

By Len Mei

Featuring case studies drawn largely from the iron and steel industries, this practical book looks at big data from a fresh perspective, and focuses on the fundamental techniques required to extract essential information from vast datasets.

By Hyunjoung Lee, Il Sohn

Authored by EMC Proven Professionals, Knowledge Sharing articles present ideas, expertise, unique deployments, and best practices. This Knowledge Sharing article provides an overview of Big Data.

By Babu Analakkat

Utilize web scraping at scale to quickly get unlimited amounts of free data available on the web into a structured format. This book teaches you to use Python scripts to crawl through websites at scale and scrape data from HTML and JavaScript-enabled pages and convert it into structured data formats.

By Jay M. Patel

Including hundreds of pages of SQL examples and explanations, this book is perfect for anyone who wants to query Hadoop with SQL and educates readers on how to create tables, how the data is distributed, and how the system processes the data.

By Jason Nolander, Tom Coffing

Showing you how to harness the power of your data and rein in the information overload, this detailed guide will help you understand the value of big data, make a business case for using Hadoop, navigate the Hadoop ecosystem, and build and manage Hadoop applications and clusters.

By Dirk deRoos, et al.

Focusing on theoretical aspects of data structures as well as their applications, this book provides a comprehensive survey of data structures of various types, and offers background information for readers with no formal training in computer science.

By Dinesh P. Mehta, Sartaj Sahni (eds)

Taking a cross-country perspective, this book offers a comprehensive view of the field including history, technicality, IT, finance, economics, legal, tax and regulatory environments, and discusses all major strategies and tactics associated with digital currencies, their uses, and their regulations.

By David Lee Kuo Chuen (ed)

Examining topics comprising functions within and throughout industrial control systems (ICS) environments, this book presents a best practices approach to securing business management environments at the strategic, tactical, and operational levels.

By Jacob Brodsky (eds), Robert Radvanovsky

This book explains how to scale Apache Spark 3 to handle massive amounts of data, either via batch or streaming processing. It covers how to use Spark's structured APIs to perform complex data transformations and analyses you can use to implement end-to-end analytics workflows.

By Alfonso Antolínez García

Including a compendium of specific case studies, the book underscores the acute need for optimization in the oil and gas exploration and production stages and shows how data analytics can provide such optimization.

By Keith R. Holdaway

Offering advice on how to interpret and incorporate data into an organization's overall marketing strategy, this practical book will help marketers seize the opportunity to see how big data can be used to understand consumers in new and exciting ways.

By Colin Strong

Providing a comprehensive framework and plan for the successful implementation of a SAP CRM, this detailed book covers the complete SAP CRM project cycle, from the prerequisites to the five phases of the SAP ASAP implementation methodology.

By Vivek Kale

Packed with tested, time-saving tips and advice, this hands-on guide will show you how to use SAP ERP Central Component 5.0 and 6.0 to create sales documents and contracts, control material and customer master data, schedule deliveries, and automate billing.

By Glynn C. Williams

Inside this book you'll get complete information on the ins and outs of the R/3 system software, including basic functions, sales document flow, invoicing, and how the S&D module interfaces with other modules.

By Glynn C. Williams

With valuable examples and practical instructions, this book provides a step-by-step implementation tutorial that equips you with high-level knowledge of configuring, deploying, extending, and integrating Splunk to bring machine-generated operational intelligence to your advantage.

By Vincent Bumgarner

With expert advice and insight, this fully updated edition demonstrates how businesses can succeed in creating a new culture of information management compliance (IMC) by incorporating an IMC philosophy into a corporate governance structure.

By Barclay Blair, Randolph Kahn

Featuring learning objectives, web resources, and discussion questions, this up-to-date book provides readers with the comprehensive knowledge necessary to understand healthcare information technology (HIT) and to hone their skills in HIT management.

By Detlev H. Smaltz, Donna J. Slovensky, Gerald L. Glandon

More and more organizations are becoming aware of the importance of tacit and explicit knowledge owned by their members which corresponds to their experience and accumulated knowledge about the firm activities. This book explains how firms can create activities to enhance identification, preservation, and use of this knowledge as a powerful mean to improve the level of economical performance of the organization.

By Camille Rosenthal-Sabroux, Faïez Gargouri (eds), Inès Saad

This title will be removed from the Skillsoft library on May 24, 2024.

By A.V. Senthil Kumar, Clive Roberts (eds), John M. Easton, Shruti Kohli

Get creative and optimize your SAP SuccessFactors Recruiting implementation with this guide, which examines a variety of integration and automation opportunities throughout the recruiting process outside of the standard integrations.

By Anand ‘Andy’ Athanur, Michael A. Wellens

This book examines the recent trend of extending data dependencies to adapt to rich data types in order to address variety and veracity issues in big data.

By Lei Chen, Shaoxu Song

Get started using Apache Spark via C# or F# and the .NET for Apache Spark bindings. This book shows you techniques that will allow you to use Apache Spark to distribute your data processing tasks over multiple compute nodes.

By Ed Elliott

This title will be removed from the Skillsoft library on May 24, 2024.

By Dhruv Kashyap, Gareth de Bruyn, Mark Balleza, Robert Lyfareff

Discover the power of SAP Integration Suite's capabilities with this hands-on guide.

By Jaspreet Bagga

With sample code and screenshots to help you fully understand JavaScript (JS), this quick guide will help you to easily master JS and develop mobile and desktop applications for SAP Fiori, while equipping ABAP/SAP developers with the essential topics to get started with JS.

By Rehan Zaidi

Addressing the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments, this comprehensive book discusses the basic concepts and tools of large-scale Big Data processing and cloud computing, and provides an overview of different programming models and cloud-based deployment models.

By Mohamed Medhat Gaber (eds), Sherif Sakr

If you work with SQL Server, dbatools is a lifesaver. This book will show you how to use this free and open source PowerShell module to automate just about every SQL server task you can imagine-all in just one month!

By Chrissy LeMaire, Cláudio Silva, Jess Pomfret, Rob Sewell

Presenting an overview on the results of the research project "LOD2 - Creating Knowledge out of Interlinked Data," a large-scale integrating project co-funded by the European Commission within the FP7 Information and Communication Technologies Work Program, this book provides a pragmatic approach for realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system.

By Sören Auer (eds), et al.

Including case studies from innovative companies that are already driving customer engagement, learning and skill development, and employee motivation with Loyalty 3.0 methods, this book reveals how to use behavioral economics, big data, social media, and gamification to inspire loyalty that lasts.

By Rajat Paharia

Utilizing flexible Learning Units comprised of tightly coupled concepts and Student Activities, the authors transport students from passively learning about IS to doing IS in a realistic context.

By Brad Prince, Hugh Watson, R. Kelly Rainer, Jr.

Explaining data quality management in practical terms, this book focuses on three key areas - the nature of data in enterprises, the purpose and scope of data quality management, and implementing a data quality management system, in line with ISO 8000-61.

By Julian Schwarzenbach, Tim King

This book contains a fast-paced introduction to data-related tasks in preparation for training models ondatasets. It presents a step-by-step, Python-based code sample that uses the kNN algorithm to manage a model on a dataset.

By Oswald Campesato

Filled with current, critical information on e-records management methods, emerging best practices, and key technologies, this book reveals step-by-step guidance for organizing, managing, protecting, and preserving electronic records.

By Robert F. Smallwood

Explaining how to configure, implement, enhance, and customize SAP OEE to address manufacturing performance management, this book will show you how to connect your business processes with your plant systems and how to integrate SAP OEE with ERP through standard workflows and shop floor systems for automated data collection.

By Dipankar Saha, Mahalakshmi Syamsunder, Sumanta Chakraborty

Helping you gain a complete and timely understanding of your customers using MDM-CDI, this comprehensive volume explains how to grow revenue, reduce administrative costs, and improve client retention by adopting a customer-focused business framework.

By Alex Berson, Lawrence Dubov

This book is for every data professional, including data engineers, ETL developers, DB administrators, Data Scientists, SQL Developers, and BI specialists. You don't need any prior expertise with this platform because the book covers all the basics.

By Anjani Kumar, Sagar Lad

Written by the leading experts in the field, this comprehensive guide shows you how to implement the SAP Business Information Warehouse (BW) and create useful applications for business analysis of company-wide data.

By Kevin McDonald, et al.

Written by SAP insiders, this comprehensive guide takes into account the ever-changing features, functionality, and toolsets of SAP NetWeaver to describe how to use SAP BW to design, build, deploy, populate, access, analyze, present, and administer data.

By Andreas Wilmsmeier, David C. Dixon, Kevin McDonald, W. H. Inmon

Including numerous SQL examples and explanations, this book details the architecture of the Azure SQL Data Warehouse and the SQL commands available, and educates readers on how to create tables and indexes, how the data is distributed, and how the system process the data.

By Todd Wilson, Tom Coffing

Focusing primarily on Microsoft and HortonWorks technologies but also covering open source tools, this timely book explains best practices, covers on-premises and cloud-based solutions, and features valuable case studies.

By Adam Jorgensen, et al.

With practical examples and detailed solutions suitable for a wide variety of applications, this unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets.

By Dominik Ryżko

This book will teach you to write interactive Spark applications using Apache Zeppelin notebooks, write and compile reusable applications and modules, and fully test both batch and streaming.

By Scott Haines

Need to stay competitive and reduce your costs? This to-the-point, user-friendly guide will help you identify and solve business problems with SAP Analytics, gain flexibility through ESA, utilize industry-specific ERP solutions, and more.

By Andreas Vogel, Ian Kimbell

Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies.

By Butch Quinto

By explaining what big data is, this book will show you how to recognize, collect, process, and analyze it; how to store and manage it; how to obtain useful information from it; and how to assess its contribution to operational, tactical, and strategic decision-making in service-oriented organizations.

By Frank Armour, J. Alberto Espinosa, Stephen H. Kaisler, William H. Money

Packed with practical examples and case studies, this detailed guide brings advanced analytics into Human Resources, giving you a framework for optimizing human capital investments through predictive analysis.

By Gene Pease

This practice-oriented book shows step by step how things can be done differently.

By Dietmar Schön

Theoretical, yet practical, this book provides a comprehensive theoretical, yet practical, look at all aspects of PLCs and their associated devices and systems.

By Rajesh Mehra, Vikrant Vij

Covering data sources such as Apache Hadoop, Azure Blob Storage, Apache Spark, Cosmos DB, and more, this book will help you keep your skills current, remain relevant, and build new business and career opportunities around Microsoft's product direction.

By Kevin Feasel

Based on real questions from author Bill Jelen's Power Excel Seminars, this lighthearted yet practical book discusses 617 of the most common and irritating problems in Excel, and provides the solutions you need to solve the problems.

By Bill Jelen

Following a learn-to-do-by-yourself approach to teaching Apache Spark using Scala, this book will help you learn the concepts, practice the code snippets in Scala, and complete the assignments given to get an overall exposure.

By Dharanitharan Ganesan, Subhashini Chellappan

Teaching you how to use the APIs and frameworks for parallel and concurrent applications in Haskell, this book will show you how to exploit multicore processors with the help of parallelism in order to increase the performance of your applications.

By Marius Mihailescu, Stefania Loredana Nita

For executives and practitioners tasked with the movement of data from old systems to a new repository, this book uses a series of steps developed in real life situations that will get the reader from an empty new system to one that is working and backed by the user population.

By Johny Morris

Use this practical guide to successfully handle the challenges encountered when designing an enterprise data lake and learn industry best practices to resolve issues.</

By Saurabh Gupta, Venkata Giri

From setting up the environment to running sample applications, this step-by-step resource is a practical tutorial on using the Apache Hadoop ecosystem project.

By Deepak Vohra

Containing many different examples from the Hadoop ecosystem, this book covers the best-practice design approaches to re-architecting your relational applications and transforming your relational data to optimize concurrency, security, denormalization, and performance.

By Bhushan Lakhe

For administrators planning a production Hadoop deployment who want to secure their Hadoop clusters, this resource takes you through a comprehensive study of how to implement defined security within a Hadoop cluster in a hands-on way.

By Bhushan Lakhe

From deploying Hive on your hardware or virtual machine and setting up its initial configuration to learning how Hive interacts with Hadoop, MapReduce, Tez and other big data technologies, this go-to resource gives you a detailed treatment of the software.

By Andreas François Vermeulen, Ankur Gupta, David Kjerrumgaard, Scott Shaw

This book is valuable for data engineers, machine learning engineers, data scientists, data architects, business analysts, and technical consultants worldwide.

By Dr. Inder Singh Gupta, Dr. Manish Gupta, Mr. Gourav Gupta

Use this practical guide to the Splunk operational data intelligence platform to search, visualize, and analyze petabyte-scale, unstructured machine data. Get to the heart of the platform and use the Search Processing Language (SPL) tool to query the platform to find the answers you need.

By Karun Subramanian

Sharing life cycle architectures, transaction path analysis frameworks, and more, this complete guide equips you with the tools and knowledge you need to address the most common enterprise architecture challenges so you can accomplish your goals in less time with fewer resources.

By James V. Luisi

Helping managers make the most of data technologies in their business area, this easy to read, in-depth guide provides readers with a solid understanding of predictive analytics, and how it should be applied to improve business decision-making and operational efficiency.

By Steven Finlay

Offering practical tips and actionable strategies for implementing more personalized marketing immediately, this book provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience.

By Dominique Levin, Ömer Artun

Including a scientific approach and data to support the theories, this book explains how to build an early warning system to identify the risk of litigation before the damage is done, and proves that there is big value in less litigation.

By Nelson E. Brestoff, William H. Inmon

Bringing a set of techniques and algorithms that are tailored to Big Data projects, this book offers case studies across a range of scientific and engineering disciplines and provides insights into semantics, identification, de-identification, vulnerabilities and regulatory/legal issues.

By Jules J. Berman

Taking you quickly to the seasoned pro level on the hottest cloud-computing framework, this book covers everything you need to build your first Hadoop cluster and begin analyzing and deriving value from your business and scientific data.

By Jason Venner, Madhu Siddalingaiah, Sameer Wadkar

Providing examples using real-time data and data-driven businesses that show you how to collect, analyze, and act in seconds, this book shows you the basics and best practices that are being adopted in Phoenix to enable a high write and read throughput in a big data space.

By Ravi Magham, Shakil Akhtar

Written from the perspective of a principal engineer with down-in-the-trenches knowledge of what to do wrong with Hadoop, this book shows how to avoid the common, expensive first errors that everyone makes with creating their own Hadoop system.

By Jason Venner

Emphasizing best practices to ensure coherent, efficient development, this book provides the right combination of architecture, design, and implementation information to create analytical systems that go beyond the basics of classification, clustering, and recommendation.

By Kerry Koitzsch

Providing specially crafted hands-on exercises covering real business scenarios, this in-depth book will help you decode the complexities and intricacies of SAP ABAP programming.

By Sushil Markandeya

Introducing use cases in each chapter from a specific industry, and using publicly available datasets from that domain to unravel the intricacies of production-grade design and implementation, this book walks you through end-to-end real-time application development using real-world applications, data, and code.

By Zubair Nabi

As most Hadoop and Big Data projects are written in either Java, Scala, or Python, this book minimizes the effort to learn another language and is written from the perspective of a .NET developer.

By Vinit Yadav

To effectively plan production costs, you know that guesswork and projections aren't enough. Optimize your production processes-and increase profitability-with this guide to production variance analysis in SAP S/4HANA.

By Janet Salmon, John Jordan

Serving as the complete reference and resource for experienced developers looking to employ Apache Hadoop in real-world settings, this guide details every aspect of Hadoop technology to enable optimal processing of large data sets, and gets you acquainted with the framework's processes and capabilities right away.

By Benoy Antony, et al.

With in-depth code examples in Java and XML and the latest on recent additions to the Hadoop ecosystem, this complete resource also covers the use of APIs, exposing their inner workings and allowing architects and developers to better leverage and customize them.

By Alexey Yakubovich, Boris Lublinsky, Kevin T. Smith

Providing a soup-to-nuts approach for a Sitecore rookie to come up to speed quickly, this unique book also offers more advanced techniques for seasoned veterans that they may not be exposed to otherwise.

By Jason Wilkerson, Phil Wicklund

Combining theoretical and technical insights into daily operations and long-term strategy, this step-by-step book acts as a development manual for practitioners seeking to conceive, develop, and manage advanced analytical models.

By Bart Baesens, Cristián Bravo, Wouter Verbeke

Taking you on an interesting journey to learn about PySpark and big data, this book uses a problem-solution approach where every problem is followed by a detailed, step-by-step answer which will improve your thought process for solving big data problems with PySpark.

By Raju Kumar Mishra

The book covers everything from basic queries to complex data-processing tasks. It begins with an introduction to SQL and Spark.

By Adam Aspin

Authored by EMC Proven Professionals, Knowledge Sharing articles present ideas, expertise, unique deployments, and best practices. This article contains an overview of how the distributed computing framework, Hadoop can be integrated with powerful search engine Solr.

By Dibyendu Bhattacharya

Including different methods that you can use to manage and maintain Cassandra and Storm, this book will teach you how to use Storm for real-time data processing and to make your applications highly available with no downtime using Cassandra.

By Shilpi Saxena

Presenting the leading-edge research in the field and the future challenges in this fledging research area, this book examines IoT applications, the design of real-time intelligent systems, and how to manage the rapid growth of the large volume of sensor data.

By Amira S. Ashour, Himansu Das (eds), Nilanjan Dey, Simon James Fong

Including a complete glossary to help readers understand the myriad terms and programming issues associated with this language, this comprehensive reference includes all the major concepts related to ABAP programming.

By Kogent Learning Solutions, Inc.

Designed as an introduction to the basics of ABAP or as a quick certification review, this book guides the reader through the intricacies of this programming language used by SAP components and applications.

By Kogent Learning Solutions, Inc.

Void of theoretical treatments and preoccupation with language syntax, this reference is a comprehensive, practical one-stop solution, which demonstrates and conveys the language's commands and features through hands on examples.

By Kaushik Roy, Sushil Markandeya

Delivering integrated management strategies covering both ABAP and Java stacks, this comprehensive, practical resource features detailed implementation, maintenance, and support information to help you get peak performance from your SAP ERP infrastructure.

By Ranjit Mereddy

Including example implementations of SAP business analytics, the challenges faced, and the solutions implemented, this book explains both the strategy and technical implementation for gathering and analyzing all the information pertaining to an organization.

By Sudipa DuttaRoy

Give your company the competitive edge by delivering up-to-date, pertinent business reports to users inside and outside your enterprise. This definitive guide shows you how to construct Enterprise Data Warehouses, create workbooks and queries, and more.

By Peter Jones

Illustrated by screenshots, diagrams, and step-by-step instructions, this guide shows you how to unleash the full potential of business intelligence with fact-based decisions, aligned to business goals, using reports and dashboards that lead from insight to action.

By Cindi Howson, Elizabeth Newbould

Including more than 450 questions and over 200 illustrations and screenshots, this book explains the important concepts and terms used in SAP Controlling (CO), and provides several consulting, configuration, and usage tips on a variety of application components within CO.

By V. Narayanan

A detailed step-by-step guide teaches you how to utilize SAP Enterprise Architecture Designer to model the four key areas: business, data, landscape, and requirements.

By Sheunopa Chalmers Musukutwa

This book covers various business scenarios from different industries including the public sector, engineering and construction, professional services, telecom, mining, chemical, and pharmaceutical.

By Joseph Alexander Soosaimuthu

Taking a jargon-free tone and providing an abundance of examples, this comprehensive and easy-to-follow resource provides a clear understanding of configuration techniques and the breadth of functionalities encompassed by SAP FICO.

By Andrew Okungbowa

Helping the reader through the most popular SAP module, this book includes material on SAP ERP Financials, SAP FICO, and SAP R/3 and covers fifty common business situations related to ERP Financials/FICO along with the practical solutions.

By S. N. Padhi

Guiding readers through the most popular SAP module, this up-to-date, quick reference covers configurations and end user transactions for validating the implementation methods, as well as provides Q&A for certification exams.

By Surya Padhi

An easy, fast, and convenient way of learning SAP FI/CO, this quick reference guide also covers ABAP and Basis on the technical side, and MM, SD, and PP on the functional side to provide a thorough understanding of the SAP system.

By V. Narayanan

Featuring an easy-to-understand Q & A format with configuration, consulting, and usage tips, this book explains the important concepts and terms used in SAP Financial Accounting (FI), and provides you with a variety of application components within FI.

By V. Narayanan

With real-world, practical examples, screenshots, menu paths, and transaction codes, this full-featured, hands-on book covers SAP's real estate management integrated solution enabling effective management of real estate and greater insight into various real estate portfolios.

By Jayant Daithankar

With essential information on the proper rules and regulations needed to comply with FAS 52, this text is a valuable reference for controllers, CFOs, IT and accounting managers, and SAP consultants who are involved in FAS 52 compliance projects.

By Susanne Finke

Beginning with a big-picture look at GRC and an explanation of how it can help your organization grow, this handbook addresses what you can do to ensure compliance; and how compliance can help you prevent fraud, bolster your corporate image, and more.

By Denise Vu Broady, Holly A. Roland

This book introduces SAP HANA Cloud and helps you develop an understanding of its key features, including technology, architecture, and data modeling. SAP HANA Cloud in a Nutshell will help you develop the skills needed to use the core features of the completely managed and in-memory cloud-based data foundation available in the SAP Business Technology Platform.

By Miguel Figueiredo

A practical guide that helps you understand the power of SAP HANA's real-time and in-memory capabilities, this book provides step-by-step instructions to exploit all the possible features of the SAP HANA database, enabling users to harness the full potential of this technology and its features.

By Chandrasekhar Mankala, Ganesh Mahadevan V.

If you are familiar with ERP products, and would like to leverage knowledge and fine-tune your configuration skills, this book begins with the basics, yet serves as a complete guide for handling real-time management and HR issues.

By Ganesh Karthik S

Showing you how to leverage the flexibility and power of SAP MII to integrate your business operations with your manufacturing processes, this book explores the important new features of the product and explains how to apply best practices to connect all the stakeholders in your business.

By Saptaparna Mukherjee (Das), Suman Mukherjee

Organized in an easy-to-understand question and answer format, this quick reference discusses the new aspects related to SAP ERP 6.0 and all the important MM codes and concepts for materials and vendors.

By Kogent Learning Solutions, Inc.

This guidebook will lead you through SAP NetWeaver, the Web services-based business integration and application platform that enables portals, collaboration, data management, development environments, and more.

By Dan Woods, Jeffrey Word

Filled with detailed descriptions, numerous illustrations, and hundreds of expert tips, this step-by-step reference provides everything you need to plan, design, install, configure, and administer SAP NetWeaver Portal.

By Rabi Jay

Taking a deep dive into common pitfalls in implementing SAP ERP projects in a complex IT landscape, this book discusses the potential causes of failures, provides a selection of relevant project implementation case studies in the area, and offers a range of possible countermeasures.

By Jayaraman Kalaimani

Providing detailed background information about the features of Project System (PS), this comprehensive volume explains how to configure PS for optimal performance, design structures and networks, create project blueprints, generate cost estimates and materials demands, and use the latest SAP tools.

By Kieron N. Dowling

Offering an easy, fast, and convenient way to learn SAP R/3 Financial transactions (v.4.6C & 4.7), this up-to-date quick reference includes coverage of General Ledger, Accounts Payable, Accounts Receivable, and Asset Accounting.

By V. Narayanan

Offering complete coverage of installation, implementation, operation, and support, this book gives full details on all of the components, including SAP Web Application Server, SAP NetWeaver, the ABAP workbench, and more.

By Franklin Martinez, Jim Keogh, Jose Antonio Hernandez

This book is a must for SAP consultants, architects, and project managers who wish to become proficient in the SAP S/4HANA project life cycle phases.

By Sudipta Malakar

A practical guide with clear and detailed examples, this book is written from the perspective of an implementation consultant and follows the path from standard to less standard, the way it should be done in an implementation project.

By Freek Keijzer

This book is your starting point for SAP S/4HANA Finance! Learn about the suite's architecture and explore its capabilities for your core finance processes: financial accounting, management accounting, treasury and risk management, planning, consolidation, and close.

By Maunil Mehta, Sam Parikh, Sanjib Chattopadhyay, Usman Aijaz

Upgrade your knowledge to learn S/4HANA, the latest version of the SAP ERP system, with its built-in intelligent technologies, including AI, machine learning, and advanced analytics.

By Andrew Okungbowa

Unlock the secrets of SAP IBP, a cloud-based powerhouse that empowers you to forecast demand with precision, optimize supply chains seamlessly, and manage inventory levels effortlessly.

By Arijit Mitra, Dr. Ankush Agrawal

This book helps SAP architects and SAP Basis administrators deploy and operate SAP S/4HANA systems on the most common public cloud platforms.

By André Bögelsack, Dhiraj Kumar, Elena Wolz, Jessica Tischbierek, Johannes Rank, Utpal Chakraborty

Providing clear advice on the inevitable, critical decisions that can lead to project success or failure, this book shows you how to fully exploit the agility SAP APO offers.

By Daniel C. Wood

Including a complete glossary of terms to help readers understand the myriad terms associated with this SAP module, this comprehensive reference features all major concepts related to SAP SD functionality, technical configuration, and implementation.

By Kogent Learning Solutions, Inc.

Designed for SAP users as a quick reference or for computer science and business students, this book includes all the major concepts related to SAP SD functionality, technical configuration, and implementation in an easy-to-understand Q&A format.

By Kogent Learning Solutions, Inc.

Providing comprehensive coverage of the essentials of SAP security currently available, this guide is designed to help the reader avoid the "gotchas" that may leave them vulnerable during times of upgrade or other system changes.

By Joey Hirao, et al.

Take an in-depth look at SAP SuccessFactors talent modules with this complete guide to configuration, administration, and best practices.

By Michael A. Wellens, Susan Traynor, Venki Krishnamoorthy

Take an in-depth look at SAP SuccessFactors talent modules with this complete guide to configuration, administration, and best practices.

By Michael A. Wellens, Susan Traynor, Venki Krishnamoorthy

By listing approximately 3800 of the most frequently used transaction codes available in the SAP system, this useful reference will enable users to quickly identify the most popular T-codes within a functional module, such as finance, controlling, materials management, human resources, payroll, quality management, and more.

By Arshad Khan

In this book, you will learn the latest cutting-edge web technologies and gain a comprehensive understanding of the user experience concept that undergirds the SAP Fiori design system.

By Marius Obert, Volker Buzek

Using a practical approach, numerous examples, and step-by-step instructions, this book will help you learn to design and build simple and advanced applications with SAP Business Workfow.

By Sudipta Malakar

Covering topics from simple to complex, this book has been written in such a way that the concepts are explained in detail, giving adequate emphasis on examples.

By Sudipta Malakar

Gain the key language concepts and programming techniques of Scala in the context of big data analytics and Apache Spark.

By Irfan Elahi

Covering real-world, concrete industry use cases, this book is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a big data project and which tools to integrate into that pattern.

By Bahaaldine Azarmi

Covering Web 3.0 technologies from a software developer's point of view, this book will be a valuable tool for anyone needing to gather, process, and publish web or database information across the modern web environment.

By Mark Watson

Preview chapters one and two of this book. This sample content shows assurance, security and risk professionals how to evaluate risks and controls in existing ERP implementations.

By ISACA

This book underlines the facilitating role of Big Data analytics, explaining why and how data analysis algorithms can be integrated operationally, in order to extract value and to improve the practices of the sharing economy.

By Mounia Khelfaoui, Soraya Sedkaoui

Making sense of big data in engineering applications using tools and techniques from signal processing, this book is ideal for professionals wanting to solve practical problems involving large amounts of data, and for students looking to grasp the fundamentals of big data analytics.

By Dan Wang, Mingyi Hong, Zhu Han

This book discusses big data forecasting for smart cities.

By Dr. Hui Liu

Presenting the analysis of leading researchers from industry and academia surrounding the pricing of network services and content, this book tackles the timely issue of surging demand for network, cloud, and content services and corresponding innovations in pricing these services to benefit consumers, operators, and content providers.

By Carlee Joe-Wong, Mung Chiang (eds), Sangtae Ha, Soumya Sen

This book covers how Snowflake's architecture is different from prior on-premises and cloud databases.

By Bhaskar B. Joshi, Bjorn Lindstrom, Frank Bell, Raj Chirumamilla, Ruchi Soni, Sameer Videkar

This Book Is for data engineers, data privacy professionals, and security teams either with security knowledge (preferably some data security knowledge) or with data engineering knowledge; in other words, either "Snowflake people" or "data people" who want to get security right, or "security people" who want to make sure that Snowflake gets handled right in terms of security

By Ben Herzberg, Yoav Cohen

Starting out with an overview of Apache Spark and the GraphX graph processing API, this example-based tutorial then teaches you how to configure GraphX and how to use it interactively.

By Michael S. Malak, Robin East

Created for experienced programmers with some background in big data or machine learning, this book teaches you the theory and skills you need to effectively handle batch and streaming data using Spark.

By Marko Bonaći, Petar Zečević

Teaching you to create end-to-end analytics applications, this entirely new book will show you interesting Java-based examples, including a complete data pipeline for processing NASA satellite data.

By Jean-Georges Perrin

With real-world production insight and expert guidance, tips, and tricks, this incredibly useful resource goes beyond general Spark overviews to provide targeted guidance toward using lightning-fast big data clustering in production.

By Brennon York, Ema Orhian, Ilya Ganelin, Kai Sasaki

A critical scholarly resource, this book brings together different methodologies that combine the potential of large data analysis with GIS applications in dedicated tools specifically for territorial, social, economic, environmental, transport, energy, real estate, and landscape evaluation.

By Angioletta Voghera, Luigi La Riccia

Consolidating SQL and the big data landscape, this in-depth guide provides a comprehensive overview, at a technology and architecture level, of different SQL technologies on big data tools, products, and solutions.

By Sumit Pal

Providing simple yet insightful quantitative techniques, this book contains essays offering detailed background, discussion, and a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.

By Bruce Ratner

Offering clear explanations and tons of step-by-step instruction to help you make sense of data mining, this plain-English guide breaks this often-overwhelming subject down into easily digestible parts, offering new and aspiring data analysts the foundation they need to be successful in the field.

By Alan Anderson, David Semmelroth

An example-driven guide to processing and analyzing real-time data streams, this immediately useful book dives into real-world case studies that show you how to scale a high-throughput stream processor, ensure smooth operation within a production cluster, and more.

By Matthew Jankowski, Peter Pathirana, Sean T. Allen

Delivering fresh content, a plethora of new examples, and over 100 hands-on exercises, this book helps you build confidence and credibility to create graphs and visualizations that make sense and weave them into action-inspiring stories.

By Cole Nussbaumer Knaflic

How can companies discover who their customers are, what they want, and how much they are willing to pay for it? Data. This book discusses how big data is transforming the creative industries, and how those industries can use lessons from Netflix, Amazon, and Apple to fight back.

By Michael D. Smith, Rahul Telang

Covering the latest advances in business intelligence such as big data, cloud, mobile, visual data discovery, and in-memory computing, this timely, up-to-date guide reveals how to plan and deploy an agile, state-of-the-art BI solution that links insight to action and delivers a sustained competitive advantage.

By Cindi Howson

Exploring a number of big data concepts and how they can be applied to improve your organization's analytics, this user-friendly handbook shows you step by step how to design, incorporate, and profit from a world-class advanced analytics ecosystem in today's big data environment.

By Bill Franks

Authored by EMC Proven Professionals, Knowledge Sharing articles present ideas, expertise, unique deployments, and best practices. This article discusses how descriptive and predictive big data analytics can drive competitiveness of Telecom operators.

By Mohamed Alaa, Mona Fahmy, Nashwa AbolFettouh

Providing much-needed industry guidance, this book contains contributions from industry leaders in the fields of SAP testing, test tool automation, and templates to help project managers and test managers establish immediate testing best practices.

By Elfriede Dustin, Jose Fajardo

Study the process of incorporating Activity-Based Costing with SAP in this insightful resource.

By Christopher F. Jackiw, Dawn J. Sedgley

Delving into the requirements for laying a solid technical and organizational foundation that is capable of supporting operational analytics at scale, this book presents everything you need to implement operational analytic processes with big data.

By Bill Franks

Using real-life examples-from Nate Silver to Copernicus, and Apple to Blackberry-to demonstrate how the winners of the future will use big data to seek the truth, this book is a comprehensive and accessible guide on how to win customers, beat competitors, and boost the bottom line with big data.

By Russell Glass, Sean Callahan

Whether a beginner or a seasoned Biml expert, this expert guide provides practical and applicable examples of Biml for automating much of the repetitive, manual labor involved in data integration.

By Andy Leonard, et al.

Based on positive and negative experiences shared by current CDOs, this practical book guides you in designing the ideal structure of a data office, implementing it, and getting the right people on board.

By Martin Treder

Providing a 360-degree view of data privacy protection using data anonymization, this book delves far beyond data anonymization techniques to supply you with the wide-ranging perspective required to ensure comprehensive protection against misuse of data.

By Balaji Raghunathan

Building on interviews and diverse case studies, this book provides an in-depth look at how data and algorithms are reshaping management practices, organizational structures, corporate culture, and work roles.

By Henri Schildt

Featuring a complete library of updated dimensional modeling techniques, this comprehensive, authoritative guide presents real-world case studies from a variety of industries, including retail sales, financial services, telecommunications, education, health care, insurance, e-commerce, and more.

By Margy Ross, Ralph Kimball

Organized for quick navigation and easy reference, this vital resource is the essential reference for data warehouse and business intelligence design, packed with best practices, design tips, and valuable insight from industry pioneer Ralph Kimball and the Kimball Group.

By Margy Ross, Ralph Kimball

Build a modern data warehouse on Microsoft's Azure Platform that is flexible, adaptable, and fast-fast to snap together, reconfigure, and fast at delivering results to drive good decision making in your business.

By Matt How

Written by a noted expert in health care innovation and management, this thorough book explores, through the lens of design thinking, how information technology will take health care into the experience economy.

By Krisa Tailor

Presenting case studies from actual projects that demonstrate how to convert theory into powerful SAP MM solutions, this book provides a complete understanding of how to best configure and implement the SAP MM module across various types of projects.

By Ashfaque Ahmed

Sharing best practices from companies that have implemented a big data strategy including Walmart, InterContinental Hotel Group, Walt Disney, and Shell, this book provides a roadmap for organizations looking to develop a profitable big data strategy, and reveals why it's not something to leave up to the IT department.

By Mark Van Rijmenam

Rife with case studies, examples, analysis, and quotes from real-world Big Data practitioners, this book provides commonsense, jargon-free advice for people and organizations looking to understand and leverage Big Data.

By Phil Simon

Offering a guide for CIO/CXOs evaluating options for various transportation management solutions available in the market, this book explains end-to-end freight life cycle processes, functional system landscape, implementation challenges and post go-live precautions required to optimize investments in SAP TM.

By Jayant Daithankar, Tejkumar Pandit

Featuring industry use cases, this practical guide reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform.

By Chris Eaton, Dirk deRoos, George Lapis, Paul C. Zikopoulos, Thomas Deutsch

Bringing together authoritative articles on the different types of information systems, this book explains how to manage real-world demands such as digital asset management, network management, digital content licensing, data quality, and information system failures.

By Marcia J. Bates (ed)

This book will show you how to organize your app's data and make it work for you and your users.

By Avi Tsadok

This book shows how dbt is used to build data transformation pipelines that enable dependency management and allow for version control and automated testing.

By Cameron Cyr, Dustin Dorsey

Providing an introduction to open source R and describes issues with traditional R and database interaction, this Oracle Press guide focuses on analyzing data with R while making it scalable using Oracle's R technologies.

By Mark Hornick, Tom Plunkett

With each chapter covering a different topic, this book targets business and IT professionals who need an introduction to business intelligence and data warehousing through a simple question/answer format.

By Arshad Khan

Focusing on examples of cloud computing, public clouds, private clouds, and virtualization, this book emphasizes how these technologies can be used to create business value and how they can be integrated into an organizations business intelligence system.

By Michael S. Gendron

The book helps you lay a very strong foundation and provides the right perspective about BI. It enables you to start or restart your journey with BI.

By Anoop Kumar V K

Explaining the principles and practical elements of BI, this guide takes you step-by-step through the technologies and the alphabet soup, so you can choose the right one and implement a successful BI environment.

By Swain Scheps

Describing best practices and pragmatic approaches so readers can put them into action, this clear and accessible book takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers.

By Rick Sherman

Including exercises and case studies with road-tested advice, this book provides ideas for improving the business performance of one's company or business functions, and emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies.

By Steve Williams

Helping you deliver business intelligence with panache, this straightforward guide will show you how to harness the power of the Reporting Services toolkit to combine charts, gauges, sparklines, indicators, and maps into compelling dashboards and scorecards.

By Adam Aspin

Placing emphasis on illustrating the underlying logic in making decisions during the cluster analysis, this book is applicable to either a course on clustering and classification or as a companion text for a first class in applied statistics.

By R.S. King

This handy guide explains how to use Crystal Reports to quickly transform almost any data into interactive content. Learn to create a simple report, and perform basic and advanced reporting features.

By Allen G. Taylor

A quick and easy guide to get you going with the latest version of this bestselling report-writing software, this book gives you just what you should know to produce the reports you'll need most often.

By Allen G. Taylor

This title will be removed from the Skillsoft library on May 24, 2024.

By Cynthia Moore

This title will be removed from the Skillsoft library on May 24, 2024.

By Jill K. Howe, et al.

This friendly guide will help you utiltize this report writer package so you can make your reports focused and readable, nest one report within another, illustrate points with charts and maps, and use it with Visual Basic, Visual C++, and Visual C#.

By Allen G. Taylor

This title will be removed from the Skillsoft library on May 24, 2024.

By David McAmis

This title will be removed from the Skillsoft library on May 24, 2024.

By Larry Rockoff

Based on the author's years of real-world experience designing solutions, this book covers all stages of data warehousing and the role of data mapping, and includes data mapping strategies and techniques that can be applied to business use cases.

By Qamar Shahbaz Ul Haq

Addressing the need, the value, and the technological means of acquiring and using information in the information age, this book provides sound and practical inputs to understand, plan and build data warehousing and data mining applications.

By Bharat Bhushan Agarwal, Sumit Prakash Tayal

Presenting various real-world case studies illustrating different techniques in rapidly growing areas, this resource is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool.

By Yanchang Zhao

Covering theory, algorithms, and methodologies, as well as data mining technologies, this authoritative reference provides a comprehensive discussion of data-intensive computations used in data mining with applications in bioinformatics.

By Pradeep Chowriappa, Sumeet Dua

Including an abundant amount of exercises and examples, this hands-on guide uses real data and actual cases to illustrate the applicability of data mining (DM) intelligence in the development of successful business models.

By Galit Shmueli, Nitin R. Patel, Peter C. Bruce

If you're serious about doing everything you can to push your company to the top, this practical book takes you step-by-step through a real-world data-mining project using open-source tools that allow you to get immediate hands-on experience working with large amounts of data.

By Meta S. Brown

Including numerous case studies throughout, this unique volume contains a collection of chapters on state-of-the-art data mining techniques applied to geoinformatic problems of high complexity and important societal value.

By Guido Cervone, Jessica Lin, Nigel Waters (eds)

Integrating theory with practical techniques and experimental results, this book provides a step-by-step breakdown of how to develop data mining tools for malware detection such as insider threat detection, firewall policy analysis, and real-time data mining.

By Bhavani Thuraisingham, Latifur Khan, Mehedy Masud

Addressing the simple fact that modern data is too big and complex to analyze in its native form, this book provides data scientists from every scientific discipline with the methods and tools to simplify their data for immediate analysis or long-term storage in a form that can be readily repurposed or integrated with other data.

By Jules J. Berman

Illustrating concepts using examples developed with commercially available products, this book explains how data virtualization servers work, what techniques to use to optimize access to various data sources, and how these products can be applied in different projects.

By Rick F. van der Lans

Emphasizing the principles of effective design, this guide reveals best practices for presenting data-driven insights with graphs, tables, maps, dashboards, and other methods that will immediately enhance corporate decision-making.

By Dan Vlamis, Tim Vlamis

Presenting a solution for creating home-grown MBA data marts, this book presents an innovative, soup-to-nuts approach that successfully combines what was previously incompatible, without degradation, and uses the relational architecture already in place.

By Fon Silvers

Authored by EMC Proven Professionals, Knowledge Sharing articles present ideas, expertise, unique deployments, and best practices. This article will demystify data warehousing, and will turn you from a novice to an informed member of an active warehouse team.

By Bruce Yellin

With extensive coverage of all data warehouse issues, ranging from basic technologies to the most recent findings and systems, this book illustrates the concepts with an on-going example based on the North wind database using Microsoft Analysis Services and Pentaho Business Analytics.

By Alejandro Vaisman, Esteban Zimányi

Providing several examples from real organizations, this book is a step-by-step how-to guide for designing and building an enterprise-wide data warehouse across a biomedical or healthcare institution, using a four-iteration lifecycle and standardized design pattern.

By Richard E. Biehl

Providing the basics of data warehousing and how it facilitates data mining and business intelligence, this guide will help you understand, develop, implement, and use data warehouses, and offers a sneak peek into their future.

By Alan R. Simon, Thomas C. Hammergren

Containing a wealth of industry examples garnered from the author's 25 years of experience, this text explores all topics needed by those who design and implement data warehouses.

By Paulraj Ponniah

Providing a unique combination of theory, applications, and technology, this informative resource supplies readers with the hands-on approach that is needed to understand the implications of theory to DSS design as well as the skills needed to construct a DSS.

By Vicki L. Sauter

Filled with expert tips and best practices, this hands-on guide shows, step-by-step, how to distribute high-performance, custom analytics to users enterprise-wide.

By Brian Larson

Demonstrating how to leverage a company's existing databases to increase profits and market share, this book provides the tools needed to thrive in today's big data world and carefully explains the most current data science methods and techniques.

By Chantal D. Larose, Daniel T. Larose

Taking a top down approach, looking at the overall architecture and then delving into the issues underlying the components, this book describes the future of data warehousing that is possible now, at both an architectural and technological level.

By Derek Strauss, Genia Neushloss, William H. Inmon

Covering best practices for managing and leading an enterprise-scale business intelligence (BI) and data warehousing (DW) program, this essential book describes what the Enterprise Program Manager must accomplish to orchestrate the many moving parts involved.

By Alan Simon

Providing clear examples of predictive analysis, this practical guide introduces the entire exciting gamut of business intelligence tools included with SQL Server 2008.

By Guy Fouche, Lynn Langit

Including selected examples and exercises, this book presents a comprehensive and systematic introduction to transforming process-oriented data into information about the underlying business process, which is essential for all kinds of decision-making.

By Stefanie Rinderle-Ma, Wilfried Grossmann

Presenting clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, this comprehensive reference discusses their application to real problems, in ways accessible and beneficial to practitioners across all industries.

By Gary Miner, John Elder, Robert Nisbet

Written for students, software professionals, and researchers, this book provides chapter summaries, review questions, and multiple-choice quizzes to explain data mining and soft computing, the fastest growing technology for the business world.

By M. Ramakrishna Murthy

If you are just starting to get a handle on Microsoft Business Intelligence (BI) tools, this book provides you with the just the right amount of information to perform basic business analysis and reporting.

By Adam Jorgensen, Brian Knight, Devin Knight, Mike Davis, Patrick LeBlanc

Accompanied by more than 550 exercises and supplements, many with complete solutions and MATLAB applications, this comprehensive volume presents the foundations of linear algebra ideas and techniques applied to data mining and related fields.

By Dan A. Simovici

Equipping you with a deeply practical, business-focused way of thinking about MDM, this book offers an understanding that will greatly enhance your ability to communicate with stakeholders and win their support.

By David Loshin

Packed with helpful tables, graphs, and charts, this practical guide provides a logical order toward planning, implementation, ongoing management, and advanced practices of Customer MDM.

By Dalton Cervo, Mark Allen

With this guide, you'll not only thoroughly learn the powerful features of Crystal Reports 9, but also how to develop custom applications to meet the specific needs of your organization.

By Cate McCoy, Gord Maric

Showing how a well-planned set of aggregates can have an extraordinary effect on the overall throughput of your data warehouse, this book offers best practices that will help you achieve astounding performance increases, while avoiding common pitfalls.

By Christopher Adamson

This text provides a complete overview of exactly what is involved in designing and building a sustainable and extensible data warehouse, and offers a how-to guide on relational and dimensional modeling in a business intelligence environment.

By Claudia Imhoff, Jonathan G. Geiger, Nicholas Galemmo

If you are a business application developer or a system analyst who has learned QlikView and Qlik Sense and now want to take your learning to the next level, this book will show you how to: tune your Qlik applications and review basic performance-tuning techniques for scalability; model your data correctly; discover a range of techniques to manage metadata; write great scripts to load data in different ways; and more.

By Stephen Redmond

Looking beyond the jargon at real business problems and common-sense solutions, this essential guide provides a much-needed step-by-step explanation of what's involved and how to use this powerful package to improve your business.

By Ken Withee

Authored by a team of Business Intelligence experts, this book introduces business analysts to the rich toolset and reporting capabilities that can be leveraged to more effectively source and incorporate large datasets in their analytics while saving them time and simplifying the reporting process.

By Bernard Wehbe, Jared Decker, Michael Alexander

Including a range of over 150 exercises to challenge even the most able student, this essential book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets.

By Anand Rajaraman, Jeffrey David Ullman, Jure Leskovec

Introducing an important niche in the text analytics field, this unified book discusses a wide swath in classical methods such as clustering, classification and topic modeling, as well as more modern text mining applications in social and information networks, and social media.

By Charu C. Aggarwal, ChengXiang Zhai (eds)

Presenting a practical introduction to the fundamental aspects of modelling and simulation, this concise guide provides the necessary foundations both for those wishing to learn about this methodology and also for those who have a need to apply it in their work.

By Gilbert Arbez, Louis G. Birta

Detailing a a comprehensive step-by-step approach to building a best practices-driven, multi-year roadmap in the quest for architecturally evolvable BI and data warehousing at the enterprise scale, this book addresses the triad of technology, work processes, and organizational/human factors considerations in a manner that blends the visionary and the pragmatic.

By Alan Simon

Using a proven methodology developed in the field, this invaluable book gives you the analytical tools, methods, and techniques to transform data you already have into information into insights that drive winning decisions.

By Andrew Wells, Kathy Chiang

Written in a business friendly style with sufficient program planning guidance, this book delivers practical advice and specific instruction to help guide planners and practitioners through the challenges of a multi-domain master data management (MDM) implementation.

By Dalton Cervo, Mark Allen

Taking readers through in a clear and logical manner using pictures and real-life examples, this book contains pages upon pages of brilliant Netezza examples, ranging from simple commands to advanced procedures.

By Mike Larkins, Tom Coffing

Demonstrating how to build sophisticated database requests and format resulting answers, this book discusses relational databases, the SQL database language, data warehousing, business intelligence (BI) and data analytics in a form that business professionals can readily understand.

By Sideris Courseware Corporation

Authored by Oracle ACE Director Mark Rittman, this Oracle Press guide will help you deliver meaningful business information to users anytime, anywhere, on any device, using Oracle Business Intelligence 11g.

By Mark Rittman

Using case studies throughout, this book highlights the practical aspects of using Oracle Essbase and Oracle Business Intelligence Enterprise Edition (OBIEE) as a comprehensive BI solution.

By Lakshman Bulusu, Rosendo Abellera

Offering a technical walkthrough of Oracle Business Intelligence Applications architecture, from the dashboard to the data source, this Oracle Press guide also provides best practices for maximizing the powerful features of each application.

By Simon Miller, William Hutchinson

With real-world examples that illustrate the powerful analysis, security, and reporting capabilities, this expert guide shows you how to optimize this intuitive ad hoc query, reporting, analysis, and web publishing tool for maximum performance.

By Darlene Armstrong-Smith, Michael Armstrong-Smith

Deliver continuous access to timely and accurate BI across your enterprise using the detailed information in this Oracle Press guide. Through clear explanations and practical examples, a team of Oracle experts shows how to assimilate data from disparate sources into a single, unified view.

By Bobby Curtis, Chris Lawless, Michelle Malcher

Written by a team of Oracle insiders, this authoritative book provides you with the most current coverage of the Oracle data warehousing platform as well as the full suite of business intelligence tools.

By Joseph Rayman, Rick Greenwald, Robert Stackowiak

Featuring series of 10 case studies that reflect the experience of Enterprises who have met today's challenges by adopting a new style of development, this book will give you the insights required to recognize the needs of your enterprise and implement Fusion solutions.

By Harish Gaur, Markus Zirn

Covering all components of the Pentaho BI Suite, this all-in-one resource will show you how to install, use, and maintain Pentaho and offers plenty of background discussion that will bring you thoroughly up to speed on BI and Pentaho concepts.

By Jos van Dongen, Roland Bouman

Taking a scenario-based approach, this insightful book focuses on the specific challenges you'll encounter when using PowerPivot, and shows you how to collect data, to mine that data through insightful analysis, and to draw conclusions that drive business performance.

By Barry Ralston

Steering readers through each point of reporting from setup, to scripting, designing, formatting, and deploying BIRT reports, this concise, practical guide will help you get results as quickly as possible.

By John Ward

Revealing the lessons known to the seasoned expert, yet rarely written down for the uninitiated, this working field manual outlines the what, when, why, and how of data mining and offers an easy-to-follow, six-step spiral process.

By Monte F. Hancock, Jr.

Including illustrations and charts, hints and tips, definitions, and case studies/examples, this accessible guide to the many advances in text analytics explains the different approaches and methods, their uses, strengths, and weaknesses, in a way that is relevant to marketing professionals.

By Steven Struhl

A comprehensive, highly technical look at the math and science behind extracting useful information from large databases.

By David Hand, Heikki Mannila, Padhraic Smyth

Presenting the principal techniques of data mining for classification, association rule mining and clustering, this practical guide clearly explains each topic and illustrates them through detailed worked examples, with a focus on algorithms rather than mathematical formalism.

By Max Bramer

Providing practical examples of cost-effective business intelligence projects, this book guides database administrators, SQL programmers, and report specialists in creating practical, cost-effective business intelligence solutions for their companies and departments.

By Caryn Mason, Randal Root

Offering a proven methodology for building reporting solutions, this thorough book presents the requirements for a real-world reporting application in a distributed environment, and covers all the phases of development.

By Kevin S. Goff, Rod Paddock

Providing solid advice for creating roles, work products, and processes, this focused guide instructs on how to organize and structure the parts of a process, and gives examples of documents you should use to define a set of processes.

By John Long

Going beyond the basics to illustrate little-known features and techniques for getting the most out of the toolset while focusing on the process of developing analytic applications, this essential guide supports the needs of the business analysts who use it, as well as the developers who support it.

By Charlie Leichtweis, Oleg Troyansky, Tammy Gibson

With a clear and concise style, a wealth of illustrations, and a focus on an ongoing example with a real industrial background, this hands-on book shows how S-BPM and its tools can be used in order to solve communication and synchronization problems involving humans and/or machines in an organization.

By Albert Fleischmann, Robert Singer, Stefan Raß

Written by a team of leading SharePoint and Business Intelligence (BI) experts, this unique book shows you how to successfully build and deliver BI applications using SharePoint 2010.

By Adam Jorgensen, Brad Schacht, Devin Knight, Mark Stacey, Patrick LeBlanc

Featuring a set of sample papers based on the pattern of DOEACC past exams, this book explains the approaches to solve a problem and addresses the various steps to develop a system.

By J.B. Dixit, Raj Kumar

Whether a beginner or a seasoned Biml expert, this expert guide provides practical and applicable examples of Biml for automating much of the repetitive, manual labor involved in data integration.

By Andy Leonard, et al.

Designed to make all readers instant experts on the architecture of Netezza, this book offers the kind of knowledge you need to make yourself an invaluable asset to your company as you master Netezza's clever design and "secret sauce" of FPGA Cards and Zone Maps.

By John Nolan, Tom Coffing

Offering a comprehensive body of knowledge on business processes, this book was written as a practical guide for executives, practitioners, managers and students by the authorities that have shaped the way we think and work with process today.

By August-Wilhelm Scheer, Henrik von Scheel, Mark von Rosing

Serving as a road map for planning, designing, building, and running the back-room of a data warehouse, this book provides complete coverage of proven, timesaving extract, transform, and load (ETL) techniques.

By Joe Caserta, Ralph Kimball

Containing a refined set of Lifecycle methods and techniques based on the authors' consulting and training experience, this toolkit walks you through the detailed steps of designing, developing, and deploying a DW/BI system.

By Ralph Kimball, et al.

Offering detailed instructions and best practices from an expert developer and trainer, this book shows you how to plan, design, construct, and administer an integrated end-to-end data warehouse/business intelligence solution to empower your users and drive better decision making.

By Robert (Bob) Laberge

Featuring a complete library of updated dimensional modeling techniques, this comprehensive, authoritative guide presents real-world case studies from a variety of industries, including retail sales, financial services, telecommunications, education, health care, insurance, e-commerce, and more.

By Margy Ross, Ralph Kimball

Including the authors' own trial-and-error experiences of building a DW/BI system with the Microsoft tools, this guide will help you get on your way to building a successful DW/BI system that supports business intelligence requirements common to most organizations.

By Joy Mundy, Ralph Kimball, Warren Thornthwaite

Presenting a clear, thorough introduction to the essentials of Petri nets, this comprehensive resource explains the core modeling techniques and analysis methods and illustrates their usefulness with examples and case studies.

By Wolfgang Reisig

Are you getting a decent return on the time and money you put into your Web site? Let this easy-to-follow guide walk you through choosing the right tools for analyzing your site, measuring data, and making changes to boost your site's profitability.

By Jennifer LeClaire, Pedro Sostre

Clearly explaining the theory behind predictive analytics, this guide teaches the methods, principles, and techniques for conducting predictive analytics projects, and offers tips and tricks that are essential for successful predictive modeling.

By Dean Abbott

Balancing a theoretical and practical approach to analyzing data within the context of serial correlation, this book emphasizes the mathematical importance of collaborative analysis of data used to collect increments of time or space.

By DeWayne R. Derryberry

Learn to use analytics more effectively, convert data into value and facilitate smarter and better decision-making for your organization.

By Jordan Morrow

Authored by EMC Proven Professionals, Knowledge Sharing articles present ideas, expertise, unique deployments, and best practices. This article documents and discusses such examples where big data analytics techniques can be used to tackle some of the difficult security challenges like Advanced Persistent Threat (APT), big ticket breaches plaguing both private and public sectors today.

By Bharath Krishnappa

This book highlights research and survey articles dedicated to big data techniques for cyber-physical system (CPS), which addresses the close interactions and feedback controls between cyber components and physical components.

By Bei Yu, Shiyan Hu

This book delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security.

By Mohammad Ahsan Chishti, Tausifa Jan Saleem

Including numerous tables, illustrations, and figures, this book presents a timely overview of cutting-edge technologies for multimedia retrieval with a special emphasis on scalability.

By Benoit Huet, Edward Y. Chang, Ioannis Kompatsiaris (eds), Stefanos Vrochidis

Exploring the unique needs of electrical utility grids, including operational technology, IT, storage, processing, and how to transform grid assets for the benefit of both the utility business and energy consumers, this book not only provides specific examples that illustrate how analytics work and how they are best applied, but also describes how to avoid potential problems and pitfalls.

By Carol L. Stimmel

Comparing and contrasting the different types of analysis commonly conducted with big data, this accessible reference presents clear-cut explanations of the general workings of big data tools.

By Kim H. Pries, Robert Dunnigan

Focusing on the business and financial value of big data analytics, this breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material.

By Frank Ohlhorst

Packed with case studies and the insights from some of the leading experts and organizations worldwide, this book shows you how to go from being data-rich to insight-rich, improving your decision making and creating competitive advantage.

By Jay Liebowitz (ed)

Using non-technical language, this book is accessible to health care professionals who might not have an IT and analytics background. It includes case studies that illustrate the business processes underlying the use of big data and health analytics to improve health care delivery.

By Harold Lehmann, Katherine Marconi (eds)

Presenting a deep insight into the realm of big data as well as the methodology, technical architecture, analytics techniques and best practices, this handbook describes the complementary nature of traditional data warehouses and big-data analytics platforms and how they feed each other.

By Harsha Srivatsa, Madhu Jagadeesh, Soumendra Mohanty

By making the topic accessible through stories, metaphors, and analogies even though it's a technical subject area, this timely book looks at cutting-edge companies supporting an exciting new generation of business analytics.

By Ambiga Dhiraj, Michael Minelli, Michele Chambers

Filled with examples that illustrate the value of analytics throughout, this book outlines a conceptual framework for data modeling that can help you immediately improve your own analytics and decision-making processes.

By Stephan Kudyba

Describing best practices and pragmatic approaches so readers can put them into action, this clear and accessible book takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers.

By Rick Sherman

Including exercises and case studies with road-tested advice, this book provides ideas for improving the business performance of one's company or business functions, and emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies.

By Steve Williams

Providing more than 100 analyses of data sets and over 600 exercises, this invaluable tool for statisticians and methodologists summarizes the latest methods for univariate and correlated multivariate categorical responses.

By Alan Agresti

Featuring detailed case examples from the financial, healthcare, and manufacturing industries, this comprehensive guide will help technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming.

By Adrian Bowles, Judith Hurwitz, Marcia Kaufman

Highlighting a range of topics such as augmented reality, ethics, and online learning environments, this essential resource demonstrates state-of-the-art approaches of advanced data mining systems in e-learning.

By Anna Visvizi (eds), Linda Daniela, Miltiadis D. Lytras, Naif Aljohani

Data and Analytics for Instructional Designers addresses what learning and performance data you need, how to design learning experiences with data collection in mind, and how to use the data to improve and evaluate those experiences.

By Megan Torrance

Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets, also covering the larger field which focuses on information, data and knowledge in the context of natural language processing.

By Asit Kumar Das, Debabrata Samanta, Saptarshi Ghosh, Soumi Dutta

Large data sets arriving at every increasing speeds require a new set of efficient data analysis techniques.

By Al-Sakib Khan Pathan (eds), Mohiuddin Ahmed

The book introduces the essentials of data science and the modern ecosystem, including the important steps such as data ingestion, data munging, and visualization.

By Chitra Lele, Dr. Gaurav Aroraa, Dr. Munish Jindal

This book gives the reader a perspective as to the overall data analytics skill set, starting with a primer on statistics, and works toward the application of those methods.

By Christopher Greco

Both engaging and informative, this book is a uniquely practical guide to increasing sales success using the power of data analytics, and shows you how to transform the corporate sales function by leveraging big data into better decision-making, more informed strategy, and increased effectiveness throughout the organization.

By Jenny Dearborn

Containing illustrations which explain how to use the outlined concepts in real-world situations, this thorough book provide readers with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification.

By Johannes Ledolter

Discussing the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates, this book includes case studies where data mining techniques have been effectively applied to advance teaching and learning

By Donald Ipperciel, Osmar R. Zaïane, Samira Elatia

This book will assist data analysts to move up from simple tools such as Excel for descriptive analytics to answer more sophisticated questions using machine learning. Most of the exercises use R and Python, but rather than focus on coding algorithms, the book employs interactive interfaces to these tools to perform the analysis.

By Andres Fortino

Applying a unified "white box" approach to data mining methods and models, this detailed second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis.

By Chantal D. Larose, Daniel T. Larose

Presenting an applied and interactive approach to data mining, this book uses engaging, real-world examples to build a theoretical and practical understanding of key data mining methods, especially predictive models for classification and prediction.

By Galit Shmueli, Mia L. Stephens, Nitin R. Patel, Peter C. Bruce

Whether investigating money laundering, insider trading, insurance fraud, or terrorist behavior, this book reviews the commonality, framework, and infrastructures necessary to implement complex analytical systems.

By Christopher Westphal

Focusing on demonstrating common business data mining applications, this book provides exposure to the data mining process, to include problem identification, data management, and available modeling tools.

By David L. Olson

Describing the benefits of data mining in business, this focused book details the process and typical business applications, the workings of basic data mining models, and demonstrates each with widely available free software.

By David L. Olson

Teaching readers everything they need to know to get going, this comprehensive resource offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations.

By Christopher J. Pal, Eibe Frank, Ian H. Witten, Mark A. Hall

Bringing together the most effective tools for solving common modeling problems, this book provides an example of each tool and describes what it is, why it is needed, and how it is generally used to model data for both databases and data warehouses.

By Steve Hoberman

Written for those involved in data preparation for analytics, this user-friendly text offers practical SAS coding tips and tricks, and provides readers with a conceptual background on data structures and considerations from the business point of view.

By Gerhard Svolba

Analytics offers many capabilities and options to measure and improve data quality, and SAS is perfectly suited to these tasks. This book focuses on selecting the right data sources and ensuring data quantity, relevancy, and completeness.

By Gerhard Svolba

Supported and explained with examples that you can replicate using open-source software, this insightful book focuses on concepts, principles and practical applications that are applicable to any industry and technology environment.

By EMC Education Services

Data is taking over in a powerful way, and it's revolutionizing the healthcare industry. This guide provides tables, checklists, and forms that allow you to take immediate action in implementing BI in your organization.

By Laura Madsen

Illustrating the steps in the book with four running case studies, this practical guide focuses on what you really need to know to create the right database for your small business and to leverage it most effectively to spur growth and revenue.

By Anna Manning

This book provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics techniques in large scale environments.

By Chattaranjan Pradhan, Himansu Das (eds), Nilanjan Dey

Addressing the key aspects of distributed processing in big data analytics, this valuable book tackles the essential concepts and patterns of distributed computing widely used in big data analytics.

By Ganesh Chandra Deka (eds), Robin Singh Bhadoria, Sourav Mazumder

Including numerous real-world case studies, this step-by-step book bridges the gap between analytics and their use in everyday marketing, providing guidance on solving real business problems using data mining techniques.

By Antonios Chorianopoulos

This title will be removed from the Skillsoft library on May 24, 2024.

By William H. Hsu (ed)

This book is a critical scholarly publication that examines the importance of data management strategies that coincide with advancements in web technologies.

By Li Yang (eds), Zongmin Ma

Providing a comprehensive overview of fog computing technology, this book explores research issues involved in the application of traditional shallow machine learning and deep learning techniques to big data analytics.

By C. S. R. Prabhu

Discussing the challenges associated with assessing student progress given the explosion of e-learning environments, this book shows educators how to effectively garner intelligent data from online educational environments that combine assessment and gamification.

By Robert Clarisó, Santi Caballé

Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation.

By Bart Baesens, Véronique Van Vlasselaer, Wouter Verbeke

Going beyond the theoretical foundation, this step-by-step book gives you the technical knowledge and problem-solving skills that you need to perform real-world multivariate data analysis.

By B. D. McCullough, Ron Klimberg

This updated and expanded third edition of Fundamentals of Predictive Analytics with JMP bridges the gap between courses on basic statistics, which focus on univariate and bivariate analysis, and courses on data mining and predictive analytics.

By Ron Klimberg

Designed to provide a complete, best practices foundation in measurement strategy, implementation, reporting, and optimization, this comprehensive book systematically demystifies the broad range of Google Analytics features and configurations.

By Eric Fettman, Feras Alhlou, Shiraz Asif

Offering an in-depth guide to improving your data integration, behavioral analysis, and ultimately, your bottom line, this book provides step-by-step guidance on using the latest analytical tools and services to gain a complete understanding of your customers, their needs, and what motivates them to take action.

By Daniel Waisberg

By helping you discover what information to track, how to choose the right goals and filters, and, most importantly, how to compile this data and use it to improve your Web site and attract more potential customers, this indispensible guide explains the concepts behind this amazing free tool.

By Jerri Ledford, Joe Teixeira, Mary E. Tyler

Using real-world examples to demonstrate current best practices and techniques, this expert guide shows you how to effectively use BigQuery, avoid common mistakes, and execute sophisticated queries against large datasets.

By Jordan Tigani, Siddartha Naidu

If you have a small business, these eight self-contained minibooks will show you how to use the Google tools that are available at little or no cost, such as Google Apps, Google search tools for business, highlighting your business, and much more.

By Bud E. Smith, Ryan Williams

Illustrated with simple examples, practice tips, and war stories based on real-world project challenges, this book provides simple rules of thumb for maintaining data provenance across the entire analytics life cycle from data extraction, through analysis to reporting.

By Enda Ridge

Including a compendium of specific case studies, the book underscores the acute need for optimization in the oil and gas exploration and production stages and shows how data analytics can provide such optimization.

By Keith R. Holdaway

Including an overview of Human Capital Management Systems (HCMS), this book provides human capital professionals, researchers, and students with a comprehensive and portable guide to human capital systems, analytics and data mining.

By Robert C. Hughes

Providing a unique view of applying human-centered computing in the social media scenario, this book looks at the classification and recognition of attributes, demographics, contexts, and correlations of human information among unconstrained visual data from the social media domain.

By Yun Fu (ed)

Showcasing numerous case studies in a variety of application areas, this thorough book provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis.

By Galit Shmueli, Ron S. Kenett

This book is for IT consultants, architects for systems and solutions, data analysts, and data analytics solution developers. All the examples in the book are based on Unix/Windows and web-based tool basic knowledge.

By Alan Bluck

Written in easy-to-understand, conversational language, this book will help you develop your digital/online marketing skills and learn web analytics to understand the performance of websites and ad campaigns.

By Todd Kelsey

Featuring concept-specific lessons, examples, step-by-step illustrations, and exercises, this book provides hands-on tutorials with just the right amount of conceptual and motivational material to illustrate how to use the intuitive interface for data analysis in JMP.

By Ann Lehman, John Sall, Lee Creighton, Mia Stephens

Julia as a Second Language introduces Julia by building on your existing programming knowledge. You'll see Julia in action as you create a series of interesting projects that guide you from Julia's basic syntax through its advanced features.

By Erik Engheim

Master core data analysis skills using Julia. Interesting hands-on projects guide you through time series data, predictive models, popularity ranking, and more.

By Bogumił Kamiński

With many tips and insights from experience professionals, this book presents research that will help shape the future of large-scale data analytics, leading the way to the design of new approaches and technologies that can analyze and synthesize very large amounts of heterogeneous data.

By Abderrahim Labbi (eds), Aris Gkoulalas-Divanis

This book is intended to present the state of the art in research on machine learning and big data analytics.

By Aboul Ella Hassanien, Ashraf Darwish

Designed specifically for those without a specialized math or statistics background, this book simplifies machine learning by focusing on two algorithm families that effectively predict outcomes, and by showing you how to apply them using the Python programming language.

By Michael Bowles

Explaining the concepts of machine learning algorithms, this practical book describes the application areas of each algorithm discussed, and uses simple, practical examples to help readers understand each algorithm.

By Eihab Bashier Mohammed Bashier, Mohssen Mohammed, Muhammad Badruddin Khan

Based on the authors' practical experience in implementing data analysis and data mining, this proven go-to guide focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects.

By Glenn J. Myatt, Wayne P. Johnson

While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management.

By Zhaohao Sun

Authored by a data analysis expert, this practical resource shows you how to tap a simple and cost-effective tool, Microsoft Excel, to solve specific business problems using powerful analytic techniques-and achieve optimum results.

By Wayne L. Winston

Containing state-of-the-art knowledge for researchers in data science, this concise book is a valuable resource for researchers and professionals working in data science, information systems and networks.

By Bo Jiang, Li M. Chen, Zhixun Su

A collection of technical and application-oriented use cases, this book enables decision makers and technologists to make connections between data analytics and such fields as virtual reality and cognitive science that are driving military organizations around the world forward.

By Kevin Huggins (ed)

Discover a variety of data-mining algorithms that are useful for selecting small sets of important features from among unwieldy masses of candidates, or extracting useful features from measured variables.

By Timothy Masters

Highlighting topics such as coding, education-based analysis, and online Delphi studies, this book explores the utilization of online platforms for setting up surveys to achieve a specific result, eliciting data in in-depth ways and applying creative analytics methods to online survey data.

By Shalin Hai-Jew (ed)

The aim of this book is to present methods based on artificial intelligence through a combination of machine learning models and symbolic approaches.

By Chloé Clavel

Packed with practical examples and case studies, this detailed guide brings advanced analytics into Human Resources, giving you a framework for optimizing human capital investments through predictive analysis.

By Gene Pease

How do visitors get to your Web site? What do they do when they get there? How can you turn visitors into customers? This practical book's case studies and step-by-step guidance demonstrate how to improve your marketing strategy with Google Analytics.

By Caleb Whitmore, Justin Cutroni, Sebastian Tonkin

Authored by a data evangelist and Google Analytics expert and the team at LunaMetrics, this book offers foundational knowledge, a collection of practical Google Tag Manager recipes, well-tested best practices, and troubleshooting tips to get your implementation in tip-top condition.

By Jonathan Weber

Including illustrations and charts, hints and tips, definitions, and case studies/examples, this accessible guide to the many advances in text analytics explains the different approaches and methods, their uses, strengths, and weaknesses, in a way that is relevant to marketing professionals.

By Steven Struhl

Including extensive case studies, most in a tutorial format, this comprehensive professional reference brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis.

By Gary Miner, et al.

This title will be removed from the Skillsoft library on May 24, 2024.

By M. Usman (eds), Muhammad Usman

Whether you are brand new to data mining or working on your tenth project, this easy-to-understand book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions.

By Bala Deshpande, Vijay Kotu

Exploring the power of predictive analytics and how you can use it to make valuable predictions for your business, this nuts-and-bolts guide helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions.

By Anasse Bari, Mohamed Chaouchi, Tommy Jung

Providing tips on outlining business goals and approaches, this friendly guide will help you discover the core of predictive analytics and get started putting it to use with readily available tools to collect and analyze data.

By Anasse Bari, Mohamed Chaouchi, Tommy Jung

Getting down to the nature of data and examining the critical issues of sources, ownership, and quality, this book offers human resource professionals the information and tools they need to harness the power of analytics and determine future outcomes.

By Jac Fitz-enz, John R. Mattox, II

Covering topics for the data scientist, Oracle developer, and Oracle database administrator, this insightful guide shows you how to get started with Oracle Data Miner and build Oracle Data Miner models using SQL and PL/SQL packages.

By Brendan Tierney

Using task-oriented descriptions and concrete end-to-end examples, this book describes all aspects of Microsoft Azure Machine Learning, from data ingress to applying machine learning, evaluating the models, and deploying them as web services.

By Roger Barga, Valentine Fontama, Wee Hyong Tok

Helping managers make the most of data technologies in their business area, this easy to read, in-depth guide provides readers with a solid understanding of predictive analytics, and how it should be applied to improve business decision-making and operational efficiency.

By Steven Finlay

Revealing the power and perils of prediction, this rich, entertaining book explores how technology literally learns from data how to predict the future behavior of individuals.

By Eric Siegel

Offering practical tips and actionable strategies for implementing more personalized marketing immediately, this book provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience.

By Dominique Levin, Ömer Artun

Providing exercises at the end of each chapter, this book offers the theory behind, programming steps for, and examples of predictive modeling with SAS Enterprise Miner.

By Kattamuri S. Sarma

Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling.

By Kattamuri S. Sarma

Chiefly focusing on concepts, techniques and methods, this book covers a large body of knowledge on process analytics - including process data querying, analysis, matching and correlating process data and models - to help practitioners and researchers understand the underlying concepts, problems, methods, tools and techniques involved in modern process analytics.

By Seyed-Mehdi-Reza Beheshti, et al.

By expertly showing the strength of the Python programming language when applied to processing, managing and retrieving information, this book will help you tackle the world of data acquisition and analysis using the power of the Python language.

By Fabio Nelli

Including in-depth case studies, this essential book teaches data analysts technologies to build an effective real-time analytics platform that can be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms.

By Byron Ellis

Including case studies and practical examples of success and failures, this is a practical guide for those who want to employ social data for analytics and business intelligence (BI), and provides a four-step approach to the social BI process that will help you access, evaluate, collaborate, and share social data with ease.

By Krish Krishnan, Shawn P. Rogers

From understanding the data and its sources to detailed metrics, dashboards, and reports, this book is a robust tool for anyone seeking a tangible return on investment from social media and digital marketing.

By Alex Gonçalves

Providing simple yet insightful quantitative techniques, this book contains essays offering detailed background, discussion, and a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.

By Bruce Ratner

Presenting a coherent, technical introduction to modern statistical learning and analytics, starting from the core foundations of statistics and probability, this book includes an overview of probability and statistical distributions, basics of data manipulation and visualization, and the central components of standard statistical inferences.

By Walter W. Piegorsch

Exploring a number of big data concepts and how they can be applied to improve your organization's analytics, this user-friendly handbook shows you step by step how to design, incorporate, and profit from a world-class advanced analytics ecosystem in today's big data environment.

By Bill Franks

Helping you derive useful insights from your data using Python, this book teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem.

By Dipanjan Sarkar

With the help of numerous real-world examples and case studies, this book takes a practical, hands-on approach to teaching you a reliable, cost-effective method to mining the vast, untold riches buried within all forms of text using R.

By Ted Kwartler

For organizations who see the value of analytics but lack the depth of knowledge needed to structure appropriate solutions, this book breaks the cycle of frustration and provides a roadmap for putting the right people, processes, and technologies into place.

By Gregory S. Nelson

Delving into the requirements for laying a solid technical and organizational foundation that is capable of supporting operational analytics at scale, this book presents everything you need to implement operational analytic processes with big data.

By Bill Franks

Providing valuable information on analysis techniques often used to derive insight from software data, this book includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source.

By Christian Bird, Tim Menzies (eds)

Drawing upon the authors' years of practical experience, and using numerous examples in the format of an easy to understand playbook, this resource presents a clear set of methods to provide reliable governance, controls, risk, and exposure management for enterprise data and the programs that rely upon it.

By Dan Meers, Gregory Lampshire, Lowell Fryman

Written by global experts in the analytics space, this accessible, non-technical book presents unstructured data analysis (UDA) concepts in a practical way, highlighting the broad scope of applications across industries, companies, and business functions.

By Jean Paul Isson

Uniquely focusing on integrating multiple types of big data intelligence into your business, this plain-English book is filled with case studies across a variety of industries and provides the essential concepts and framework to implement business analytics.

By Jean Paul Isson, Jesse Harriott

Providing cross-disciplinary perspectives on text mining and its applications, this book offers focused studies describing text mining on historical texts, automated indexing using constrained vocabularies, and the use of natural language processing to explore the climate science literature.

By Emma L. Tonkin, Gregory J.L. Tourte (eds)

This book covers a multitude of data processing challenges, ranging from the simple to the complex.

By Chanchal Chatterjee

Advanced analytics is a mixture of machine learning, artificial intelligence, graphs, text mining, data mining, semantic analysis.

By Amit Kumar Tyagi, Archana Mire, Shaveta Malik

Develop and optimize deep learning models with advanced architectures, this book teaches you the intricate details and subtleties of the algorithms that are at the core of convolutional neural networks.

By Umberto Michelucci

Containing practical real-world examples of data analytics, this book will provide you with a broad foundation of advanced data analytics concepts and knowledge of the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB.

By Sayan Mukhopadhyay

This book presents the state of the art in the acquisition and analysis of 3D and high-resolution fingerprints. Based on the authors' research, this book focuses on advanced fingerprint recognition using 3D fingerprint f

By David Zhang, Feng Liu, Qijun Zhao

Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5-10 years. The book provides clear explanations of principles and algorithms supported with applications.

By E. R. Davies, Matthew Turk

Providing an overview of challenging areas and descriptions of novel algorithms, this authoritative book presents a broad selection of cutting-edge research, covering both theoretical and practical aspects of reconstruction, registration, and recognition.

By Giovanni Maria Farinella, Roberto Cipolla (eds), Sebastiano Battiato

Advances in Deep Learning Applications for Smart Cities provides a global perspective on current and future trends concerning the integration of deep learning and blockchain for smart cities. It provides valuable insights on the best practices and success factors for smart cities.

By Rajeev Kumar, Rakesh Kumar Dwivedi

With step-by-step clarity and purpose, this one-of-a-kind, practical guidebook is your go-to resource of authoritative insight into using advanced machine learning solutions to overcome real-world investment problems.

By Marcos López de Prado

In this book, we review the latest developments in adversarial attack technologies in computer vision; natural language processing; and cybersecurity with regard to multidimensional, textual and image data, sequence data, and temporal data.

By Aneesh Sreevallabh Chivukula, Bo Liu, Wanlei Zhou, Wei Liu, Xinghao Yang

Cover classical algorithms commonly used as artificial intelligence techniques and program agile artificial intelligence applications using Pharo. This book takes a practical approach by presenting the implementation details to illustrate the numerous concepts it explains.

By Alexandre Bergel

This book presents the astonishing potential of deep sensorimotor policies for agile vision-based quadrotor flight.

By Antonio Loquercio

Teaching you how to deliver superior data products through agile processes, this book shows you, through example, how to organize and manage a fast-paced team challenged with solving novel data problems at scale, in a production environment.

By Eric Carter, Matthew Hurst

This book focuses on all these topics, including a few case studies, and they give a clear indication as to why these techniques should now be widely adopted by the agriculture and farming industries.

By Amitava Choudhury, Amlan Chakrabarti, Arindam Biswas, Manish Prateek

This book presents state-of-the-art blockchain and AI advances in health care. Healthcare service is increasingly creating the scope for blockchain and AI applications to enter the biomedical and healthcare world.

By Bipin Kumar Rai, Gautam Kumar, Vipin Balyan

This book offers a groundbreaking approach to bridging the gap between various disciplines involved in cognitive modeling in education.

By Andrej Flogie, Boris Aberšek, Igor Pesek

Written for a wide reading audience who all share the goal of shaping AI-informed products and services, this book provides context for AI that is rare to find today: how to learn from AIs past to shape it for today and the future.

By Gavin Lew, Robert M. Schumacher Jr.

With easy-to-digest instruction and two complete hands-on serverless AI builds, this must-read guide is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory.

By Eóin Shanaghy, Peter Elger

AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI provides readers with solutions and a foundational understanding of the methods that can be applied to test AI systems and provide assurance.

By Feras A. Batarseh, Laura Freeman

AI Computing Systems: An Application Driven Perspective adopts the principle of "application-driven, full-stack penetration" and uses the specific intelligent application of "image style migration" to provide students with a sound starting place to learn.

By Ling Li, Qi Guo, Wei Li, Yunji Chen, Zichen Xu, Zidong Du

This book will give you a clear understanding of how the healthcare system works and how to apply ML and deep learning tools and techniques to the healthcare industry.

By Anshik

This book is divided into two parts, the first of which describes AI as we know it today, in particular the Fintech-related applications.

By Federico Cecconi

This book guides you through each step, from defining the business need and business model, all the way to registering IP and calculating your AI start-up valuation.

By Adhiguna Mahendra

This book explains and illustrates recent developments and advances in decision-making and risk analysis.

By Louis Anthony Cox Jr.

Guiding you through setting up your Alexa-enabled device so you don't have to ask the kids, this book shows the senior reader how to use Alexa to help with everyday tasks, will give you peace of mind and keep you safe.

By Nick Vandome

Featuring a collection of authoritative articles by leaders in the field, this in-depth reference focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and Artificial Intelligence (AI) methods.

By Jianxin Wang, Min Li (eds), Yi Pan

This book teaches the most important approaches to algorithmic web data analysis, enabling you to create your own machine learning applications that crunch, munge, and wrangle data collected from users, web applications, sensors and website logs.

By Dmitry Babenko, Douglas G. McIlwraith, Haralambos Marmanis

Presenting basic ideas of machine learning in a way that is easy to understand, this book provides hands-on practical advice, uses simple examples, and motivates students with discussions of interesting applications.

By Miroslav Kubat

This book is a comprehensive guide for agricultural and meteorological predictions. It presents advanced models for predicting target variables.

By Akram Seifi, Fatemeh Barzegari Banadkooki, Mohammad Ehteram

Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity provides machine and deep learning methods for analysis and characterization of events regarding privacy and anomaly detection as well as for establishing predictive models for cyber attacks or privacy violations.

By Anacleto Correia, Victor Lobo

Modern AI applications are not built from scratch but by integrating off-the-shelf components: libraries, frameworks, and services. This insightful resource focuses on engineering user friendly, high-performance, and maintainable AI applications.

By Bernhard G. Humm

This book is designed so that you can focus on the parts you are interested in. You will explore topics as regularization, optimizers, optimization, metric analysis, and hyper-parameter tuning.

By Umberto Michelucci

With complete and complex examples throughout, this book will teach you how to work with advanced topics in deep learning, and will show you strategies to address typical problems encountered when training deep neural networks.

By Umberto Michelucci

Deep Learning has become increasingly important due to the growing need to process and make sense of vast amounts of data in various fields. If you want to gain a deeper understanding of the techniques and implementations of deep learning, then this book is for you.

By Dr. Neeraj Kumar, Dr. Rajkumar Tekchandani

Accompanied by practical step-by-step Python code samples and Jupyter notebooks, this comprehensive guide acts as a reference for a data scientist, machine learning practitioner or anyone interested in AI applications.

By Kevin Ashley

Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation.

By Taweh Beysolow II

Implement deep learning applications using TensorFlow while learning the "why" through in-depth conceptual explanations.

By Orhan Gazi Yalçın

Looking toward the next frontier in computing: interactive, partly intelligent, meticulously designed physical environments, this book examines how these architectural robotic systems will support and augment us at work, school, and home, as we roam, interconnect, and age.

By Keith Evan Green

This book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high-level natural language processing technology.

By Mathilde Janier, Patrick Saint-Dizier

This book explores the complex topic of AI ethics in a cross-functional way, alternating between theory and practice. Practical and recent events, and their associated challenges, are presented, such as the collateral effects of the COVID-19 pandemic on the application of AI technologies.

By Dr Julie E. Mehan

This book provides theoretical background and state-of-the-art findings in artificial intelligence and cybersecurity for industry 4.0 and helps in implementing AI-based cybersecurity applications.

By Danilo Pelusi, Joy Iong-Zong Chen, Velliangiri Sarveshwaran

Including real-world success and failure stories, this book aims to help readers understand the concept of artificial intelligence and deep learning methods and how to implement them into their businesses and organizations.

By Jagreet Kaur, Navdeep Singh Gill

Providing a general introduction to the various branches of AI, this book is designed to identify some of the current applications and techniques of artificial intelligence as an aid to solving problems and accomplishing tasks.

By Garima Nagpal, Itisha Gupta

Artificial Intelligence and Industry 4.0 explores recent advancements in blockchain technology and artificial intelligence (AI) as well as their crucial impacts on realizing Industry 4.0 goals.

By Aboul Ella Hassanien, Jyotir Moy Chatterjee, Vishal Jain

Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing.

By Neeraj Kumar Singh, Parul Verma, Rajiv Pandey, Sunil Kumar Khatri

Over the past decade, Artificial Intelligence has proved invaluable in a range of industry verticals such as automotive and assembly, life sciences, retail, oil and gas, and travel. The leading sectors adopting AI rapidly are Financial Services, Automotive and Assembly, High Tech and Telecommunications. Travel has been slow in adoption, but the opportunity for generating incremental value by leveraging AI to augment traditional analytics driven solutions is extremely high.

By Ben Vinod

Offering insight into solving some well-known AI problems using the most efficient problem-solving methods by humans and computers, this book discusses the importance of developing critical-thinking methods and skills, and develops a consistent approach toward each problem.

By Christopher Pileggi, Danny Kopec, David Ungar, Shweta Shetty

An essential reference source that discusses applications of artificial intelligence, machine learning, and data mining, this book discusses other tools and strategies to protect networks against security threats and solve security and privacy problems.

By Ryma Abassi

This book explores AI from that angle and is aimed at testing and quality management practitioners who want to understand more, starting with the relationship between AI and trustworthiness, the issue of bias, and the complexities of testing machine learning systems.

By Adam Leon Smith, James Davenport, Jeremias Rößler, Joanna Olszewska, Jonathon Wright, Rex Black

In this book the editors put forward two core propositions: creative artistic behavior is one of the key challenges of artificial intelligence research, and computer-assisted creativity and human-centered artificial intelligence systems are the driving forces for research in this area.

By Gary Greenfield, Juan Romero, Penousal Machado

This book covers the features of modern Field Programmable Gate Arrays (FPGA) devices, design techniques, and successful implementations pertaining to AI applications.

By Anuradha D. Thakare, Sheetal Umesh Bhandari

This title will be removed from the Skillsoft library on May 24, 2024.

By Farid Meziane, Sunil Vadera

This book discusses all aspects of money laundering, starting from traditional approach to financial crimes to artificial intelligence-enabled solutions. It also discusses the regulators approach to curb financial crimes and how syndication among financial institutions can create a robust ecosystem for monitoring and managing financial crimes.

By Abhishek Gupta, Dwijendra Nath Dwivedi, Jigar Shah

Designed as a self-teaching introduction to the fundamental concepts of artificial intelligence, this book's coverage includes searching processes, knowledge representation, machine learning, expert systems, programming, and robotics.

By Neeru Gupta, Ramita Mangla

This book has arrived to equip you with a fundamental, timely grasp of AI and its impact.

By Tom Taulli

Through various case studies that the reader will understand and benefit from, this book aims to help readers understand, learn, define problems, and architect AI projects.

By Archie Addo, Muthu Shanmugam, Srini Centhala

The book begins by examining the fundamental concepts of AI ethics and its recognition within international law. It then delves into the challenges of governing AI in a rapidly evolving technological landscape, highlighting the need for pragmatic and flexible approaches to AI regulation.

By Abhivardhan

With examples in C# that can easily be applied across a wide range of platforms, including web, desktop, and mobile, this book is your accessible and practical guide to building AI-powered applications using the easy-to-use Cognitive Services APIs from Microsoft.

By Nishith Pathak

This title will be removed from the Skillsoft library on May 24, 2024.

By Dimitris Vrakas, Ioannis PL. Vlahavas (eds)

This book explains how artificial Intelligence for Asset Management and Investment makes this difficulty a thing of the past, providing you with a professional and accessible framework for setting up and running artificial intelligence in your financial operations.

By Al Naqvi

Accounting and auditing firms need a comprehensive framework for intelligent, automation-centric modernization. This book delivers just that-a plan to evolve legacy firms by building firmwide AI capabilities.

By Al Naqvi

Outlining the new frontiers for autonomous networks, this invaluable resource highlights their impact and benefits to consumers and enterprise customers

By Mazin Gilbert (ed)

This book provides a concise introduction to the essential aspects of using artificial intelligence methods for business analytics, presents machine learning and the most important algorithms in a comprehensible form using the business analytics technology framework, and shows application scenarios from various industries.

By Felix Weber

Helping with the identification of which business problems and opportunities are right for AI, this book provides the reader with an easy to understand roadmap for how to take an organization through the adoption of AI technology.

By Jason L. Anderson, Jeffrey L. Coveyduc

Making AI more accessible than ever, this hands-on book provides a clear overview of the technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field.

By John Paul Mueller, Luca Massaron

Starting with a basic definition of AI and explanations of data use, algorithms, special hardware, and more, this reference simplifies this complex topic for anyone who wants to understand what operates the devices we can't live without.

By John Mueller, Luca Massaron

With an application focused approach, this book provides real-world examples, breaks down technical jargon for non-technical readers, and provides an educational resource for fashion professionals.

By Leanne Luce

Including examples from over 100 real games, and 10 in-depth case studies, this comprehensive, professional tutorial walks through the entire development process from beginning to end, and introduces many techniques little-used by developers today.

By Ian Millington, John Funge

This book explains about Artificial Intelligence.

By Otmar Hilliges, Yang Liu

This book provides a brief synthesis of the known implementations, opportunities and challenges at the intersection of artificial intelligence (AI) and modern industry beyond the big-four companies that traditionally consume and produce such advanced technology: Facebook, Amazon, Microsoft and Google.

By Mayank Kejriwal

Critically assess the impact of artificial intelligence on the L&D function and understand how to use it to improve learning in the workplace.

By Donald Clark

The book offers unique managerial frameworks to guide an organization's AI journey. The first section looks at what AI is; and how you can prepare for it, decide when to use it, and avoid pitfalls on the way. The second section dives into the different AI techniques and shows you where to apply them in business. The final section then prepares you from a strategic AI leadership perspective to lead the future of organizations.

By Malay A. Upad

A straightforward, non-technical guide to the next major marketing tool, this practical book will explain how Artificial Intelligence and Machine Learning will revolutionize your company's marketing strategy, and teach you how to use it most effectively.

By Jim Sterne

Explaining how to use AI to manage risk in the corporate environment, this book defines risk, provides examples, and includes information on the risk-management process.

By Archie Addo, Muthu Shanmugam, Srini Centhala

Exploring terminologies of security and how AI can be applied to automate security processes, this book provides practical examples and real-time use cases, as well as detailed explanations and recommendations for how implement procedures.

By Archie Addo, Muthu Shanmugam, Srini Centhala

The objective of this book is to leverage the significance of artificial intelligence in achieving sustainable solutions using interdisciplinary research through innovative ideas.

By B. Vinoth Kumar, K. Umamaheswari, S. K. Somasundaram

Considering the foundations, metrics and applications of Internet of Everything (IoE) systems, this book covers whether devices and IoE systems should speak only to each other, to humans or to both.

By Donald Sofge, Ira S. Moskowitz, Ranjeev Mittu, Stephen Russell (eds), William Lawless

You will delve into the theory behind AI and machine learning projects, examining techniques for learning from data, the use of neural networks and why algorithms are so important in the development of a new AI agent or system.

By Andrew Lowe

This book discusses a number of critical issues, such as AI ethics and privacy, the development of a conscious mind, and autonomous robotics in our daily lives.

By Raymond S. T. Lee

This book will use artificial intelligence to explain what these economic and finance theories mean in the context of the agent wanting to make a decision.

By Moloi

This book presents a systematic evolution of artificial intelligence (AI), its applications, challenges and solutions in the field of healthcare. The book mainly covers the foundations and various methods of learning in artificial intelligence with its application in healthcare industry.

By Basanta Barman, Jyotismita Talukdar, Thipendra P. Singh

Artificial Intelligence in Industry 4.0 and 5G Technology helps readers solve real-world technological engineering optimization problems using evolutionary and swarm intelligence, mathematical programming, multi-objective optimization, and other cutting-edge intelligent optimization methods.

By Elias Munapo, Gerhard-Wilhelm Weber, J. Joshua Thomas, Pandian Vasant

The book covers ways to use neural networks to classify patients with diseases. You will know how to apply computer vision techniques and convolutional neural networks (CNNs) to segment diseases such as cancer (e.g., skin, breast, and brain cancer) and pneumonia.

By Tshepo Chris Nokeri

Presenting 50 case studies of actual situations, this book is a fascinating look into how companies use AI and machine learning to solve problems.

By Bernard Marr, Matt Ward

This third edition provides a comprehensive, colorful, up-to-date, and accessible presentation of AI without sacrificing theoretical foundations.

By Danny Kopec, Sarhan M. Musa, Stephen Lucci

With contributions from pioneers and experts in the field of neural networks, this book covers the major basic ideas of brain-like computing behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as future alternatives.

By Cesare Alippi, Francesco Carlo Morabito (eds), Robert Kozma, Yoonsuck Choe

Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines.

By Cesare Alippi, Francesco Carlo Morabito, Robert Kozma, Yoonsuck Choe

Cutting through much of the murky language, the jargon, recondite formulations, and even utter nonsense surrounding this field, this accessible book will give you the practical information and pointers on applications that you need to know to succeed.

By Steven Struhl

Artificial Intelligence Methods for Optimization of the Software Testing Process: With Practical Examples and Exercises presents different AI-based solutions for overcoming the uncertainty found in many initial testing problems.

By Leo Hatvani, Sahar Tahvili

Discussing the importance of developing critical-thinking methods and skills, and developing a consistent approach toward each problem, this book lends insight into solving some well-known artificial intelligence (AI) problems using the most efficient methods by humans and computers.

By Christopher Pileggi, Danny Kopec, Shweta Shetty

The book demystifies artificial intelligence and teaches readers its fundamentals from scratch in simple and plain language and with illustrative code examples.

By Perry Xiao

Including contributions from leading scholars in a diverse set of fields, this resource is comprised of chapters addressing different aspects of the AI control problem as it relates to the development of safe and secure artificial intelligence.

By Roman V. Yampolskiy

The book will be of interest to both newcomers and experienced scientists working in the fields of satellite image processing, geo-engineering, remote sensing and Artificial Intelligence.

By D. Jude Hemanth

This title will be removed from the Skillsoft library on May 24, 2024.

By Pedro Isaías (eds), Tomayess Issa

This book explains the appropriation of artificial intelligence by military organizations, but also law enforcement agencies and the police; to discuss the questions that the development of artificial intelligence.

By Daniel Ventre (ed)

Introducing advanced beginners to basic machine learning and deep learning concepts and algorithms, this book is intended to be a fast-paced introduction to various "core" features of machine learning and deep learning, with code samples that are included in a university course.

By Oswald Campesato

To be able to merge the psyche with the neural system has been a long-sought goal. There is much scientific literature on results from research on this topic, but the goal of this "booklet" is to present the subject in a nutshell and to attract a wider audience to this highly complex topic.

By Dietmar Dietrich

Offering students and AI programmers a new perspective on the study of artificial intelligence concepts, this book has numerous up-to-date applications in game programming, intelligent agents, neural networks, artificial immune systems, and more.

By M. Tim Jones

This title will be removed from the Skillsoft library on May 24, 2024.

By Information Resources Management Association (IRMA)

Providing insight into various social and ethical issues, this book is a simple, explanatory, and descriptive guide for developers, technology consultants, and those interested in AI who want to understand the fundamentals of AI and implement it practically by devising smart solutions.

By Prabhat Kumar

Wireless communication and networking based on AI concepts and techniques are explored in this book, specifically focusing on the current research in the field by highlighting empirical results along with theoretical concepts.

By K. Ananthajothi, R. Kanthavel, R. Karthik Ganesh, S. Balamurugan

This book presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods.

By Alma Y. Alanis, Carlos López-Franco (eds), Nancy Arana-Daniel

Showing you how to use Java to develop neural network applications, this practical book uses a step-by-step approach including plenty of examples, diagrams, and screenshots to facilitate your learning experience.

By Igor Livshin

Develop machine learning models across various domains. This book offers a single source that provides comprehensive coverage of the capabilities of TensorFlow 2 through the use of realistic, scenario-based projects.

By Poornachandra Sarang

This book includes practical examples illustrating automated deep learning approaches and provides techniques to facilitate your deep learning model development.

By Ivan Gridin

"Automated Machine Learning in Action" reveals how you can automate the burdensome elements of designing and tuning your machine learning systems.

By Haifeng Jin, Qingquan Song, Xia Hu

Understand the current and future research into technologies that underpin the increasing capabilities of automation technologies and their impact on the working world of the future.

By Peter Matthews, Steven Greenspan

Discussing many aspects of field robotic systems, this book provides a new framework and the related algorithms for designing autonomous mobile robotic systems in unknown outdoor environments.

By Chunxin Qiu, Mark Andrew Minor, Xiaorui Zhu, Youngshik Kim

Written by world-class researchers and scientists, this book explores how Artificial Intelligence (AI), by leading to an increase in the autonomy of machines and robots, is offering opportunities for an expanded but uncertain impact on society by humans, machines, and robots.

By Donald Sofge, Ranjeev Mittu, Stephen Russell (eds), W.F. Lawless

Employing a modern computational approach known as Markov chain Monte Carlo (MCMC), this book provides an analytical structure for combining data and information from various sources to generate estimates of the parameters of uncertainty distributions used in risk and reliability models.

By Curtis Smith, Dana Kelly

Providing numerous examples that involve the use of particle filters, this book views multiple target tracking as a Bayesian inference problem and within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking.

By Kristine L. Bell, Lawrence D. Stone, Roy L. Streit, Thomas L. Corwin

Bayesian Optimization in Action teaches you how to create efficient machine learning processes using a Bayesian approach.

By Quan Nguyen

Opening a discussion about uncertainty in model parameters, model specifications, and model-driven forecasts in a way that standard statistical risk measurement does not, this book provides a roadmap to better risk management through more circumspect measurement, with comprehensive treatment of model uncertainty.

By Matt Sekerke

With an expansion of case studies that detail Bayesian solutions for a variety of applications, this comprehensive resource presents the Bayesian approach to statistical signal processing for a variety of useful model sets.

By James V. Candy

Detailing the advantages of the Bayesian approach and nature of the computational revolution, this unique book provides a platform for researchers in marketing to analyze data with state-of-the-art methods and develop new models of consumer behavior.

By Greg M. Allenby, Peter E. Rossi, Robert McCulloch

Providing a comprehensive look at all the major bot frameworks available, this book will teach you the basics for each framework helping you to get a clear picture for which one is best for your needs.

By Manisha Biswas

Providing a gentle introduction to the world of Artificial Intelligence (AI) using the Raspberry Pi as the computing platform, this book explores most of the major AI topics, including expert systems, machine learning both shallow and deep, fuzzy logic control, and more.

By Donald J. Norris

You'll start with an introduction to AI, where you'll learn the history of neural networks and what sets deep learning apart from other varieties of machine learning.

By Liangqu Long, Xiangming Zeng

Game developers will use this book to gain a basic knowledge of programming artificial intelligence using Unity and C#. You will not be bored learning the theory underpinning AI. Instead, you will learn by experience and practice, and complete an engaging project in each chapter.

By Sebastiano M. Cossu

Using JavaScript programming features along with standard libraries, this book takes advantage of the intricacies of the ML processes by using a simple, flexible and portable programming language to work with more approachable, fundamental coding ideas.

By Nagender Kumar Suryadevara

Integrate MLOps principles into existing or future projects using MLFlow, operationalize your models, and deploy them in AWS SageMaker, Google Cloud, and Microsoft Azure. This book guides you through the process of data analysis, model construction, and training.

By Sridhar Alla, Suman Kalyan Adari

This book explains about Tensorflow.

By Mohan Kumar Silaparasetty

Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency.

By Jared Dean

The brain-computer interface (BCI) is an emerging technology that is developing to be more functional in practice. The aim is to establish, through experiences with electronic devices, a communication channel bridging the human neural networks within the brain to the external world.

By Balamurugan Balusamy, Chandran Venkatesan, M.G. Sumithra, Mariofanna Milanova, Rajesh Kumar Dhanaraj

Taking you through the history of chatbots, including when they were invented and how they became popular, this book will show how to build a chatbot for your next project using best practices and focusing on the technological implementation and UX.

By Anik Das, Rashid Khan

Containing real examples that you can implement and modify to build useful computer vision systems, this book will teach you to apply computer vision and machine learning concepts in developing business and industrial applications using a practical, step-by-step approach.

By Shamshad Ansari

Teaching you about leveraging machine learning in practice, this book covers everything you need to produce a fully functioning Intelligent System, one that leverages machine learning and data from user interactions to improve over time and achieve success.

By Geoff Hulten

Using a systematic approach, this resource is a one-stop shop that takes the beginner on a journey to understanding the theoretical foundations and the practical steps for leveraging machine learning and deep learning techniques on problems of interest.

By Ekaba Bisong

This book introduces a Responsible AI framework and guides you through processes to apply at each stage of the machine learning (ML) life cycle, from problem definition to deployment, to reduce and mitigate the risks and harms found in artificial intelligence (AI) technologies.

By Toju Duke

Showing how you can use bots for just about everything, this book teaches you about bot programming, using all the latest and greatest programming languages, including Python, Go, and Clojure, so you can feel at ease writing your Telegram bot in a way that suits you.

By Nicolas Modrzyk

Offering high value to a multitude of audiences, this book aims to capture the viewpoints of thought leaders from around the world and share their ideas on business strategy formation in a world of artificial intelligence.

By Al Naqvi (eds), J. Mark Munoz

If you are a developer interested in learning how to build your own conversational bot from scratch, this book is for you. Upon completion, you will be able to build a text-based Facebook Messenger bot and a voice-based custom skill for Amazon's Alexa Voice Service.

By Amit Kothari, Joshua Hoover, Rania Zyane

ChatGPT For Dummies demystifies the artificial intelligence tool that can answer questions, write essays, and generate just about any kind of text it's asked for. This powerful example of generative AI is widely predicted to upend education and business. In this book, you'll learn how ChatGPT works and how you can operate it in a way that yields satisfactory results.

By Pam Baker

Using machine learning and artificial intelligence (AI) in existing business processes has been successful. Even AWS's ML and AI services make it simple and economical to conduct machine learning experiments. This book will show readers how to use the complete set of AI and ML services available on AWS to streamline the management of their whole AI operation and speed up their innovation.

By David Bounds, Premkumar Rangarajan

This book is to provide the most relevant information on Human-Computer Interaction to academics, researchers, and students and for those from industry who wish to know more about the real-time application of user interface design.

By Rohit Raja, Sandeep Kumar, Shilpa Rani, Shrikant Tiwari

Featuring detailed case examples from the financial, healthcare, and manufacturing industries, this comprehensive guide will help technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming.

By Adrian Bowles, Judith Hurwitz, Marcia Kaufman

This edited book designs the Cognitive Computing in Human Cognition to analyze to improve the efficiency of decision making by cognitive intelligence. The book is also intended to attract the audience who work in brain computing, deep learning, transportation, and solar cell energy.

By Amiya Ranjan Panda, Pradeep Kumar Mallick, Prasant Kumar Pattnaik, Valentina Emilia Balas

Highlighting a range of topics such as augmented reality, ethics, and online learning environments, this essential resource demonstrates state-of-the-art approaches of advanced data mining systems in e-learning.

By Anna Visvizi (eds), Linda Daniela, Miltiadis D. Lytras, Naif Aljohani

This book gives a cognitive approach to the IoT provides connectivity to everyone and everything since IoT connected devices are known to increase rapidly. When the IoT is integrated with cognitive technology, performance is improved, and smart intelligence is obtained.

By E. Vamsidhar, G. R. Kanagachidambaresan, Kolla Bhanu Prakash, V. Srikanth

Follow a step-by-step, hands-on approach to building production-ready enterprise cognitive virtual assistants using Google Dialogflow.

By Amit Agrawal, Navin Sabharwal

This book addresses the key security challenges in the big data centric computing and network systems, and discusses how to tackle them using a mix of conventional and state-of-the-art techniques.

By Al-Sakib Khan Pathan, Zubair Md. Fadlullah (eds)

This book focuses on the sophisticated methods for improving dye extraction and dyeing properties which will minimize the use of bioresource products. This book also brings out the innovative ways of wet chemical processing to alleviate the environmental impacts arising from this sector.

By Amit Kumar Tyagi

Written to benefit patients without adding to the already high medical costs, this book is for both medical imaging professionals to acquire and interpret the data, and computer vision professionals to provide enhanced medical information by using computer vision techniques.

By C. H. Chen (ed)

Focusing on computer vision as on-board technology, this essential resource brings together fields of research where computer vision is progressively penetrating the automotive sector, unmanned aerial and underwater vehicles.

By Antonio M. López, Atsushi Imiya, Jose M. Álvarez, Tomas Pajdla

Design and develop end-to-end, production-grade computer vision projects for real-world industry problems. This book discusses computer vision algorithms and their applications using PyTorch.

By Adarsha Shivananda, Akshay Kulkarni, Nitin Ranjan Sharma

Organizations spend huge resources in developing software that can perform the way a human does. Image classification, object detection and tracking, pose estimation, facial recognition, and sentiment estimation all play a major role in solving computer vision problems.

By Vaibhav Verdhan

Harness the untapped potential of combining a decentralized Internet of Things (IoT) with the ability to make predictions on real-world fuzzy data. This book covers the theory behind machine learning models and shows you how to program and assemble a voice-controlled security.

By Fabio Manganiello

This title will be removed from the Skillsoft library on May 24, 2024.

By Information Resources Management Association (IRMA)

With classroom-tested programming exercises and review questions, this easy-to-read book provides an accessible general introduction to the essential topics in computer vision, highlighting the role of important algorithms and mathematical concepts.

By Reinhard Klette

This book offers a brief but effective introduction to quantum machine learning (QML).

By Davide Pastorello

This book explains the principles and applications of artificial intelligence for a broad audience.

By Athanasios Karapantelakis, Elena Fersman, Paul Pettersson

This book is for MLOps, DevOps, Machine Learning Engineers, and Data Scientists who want to continuously deploy machine learning pipelines and manage them at scale using Kubernetes. The readers should have a strong background in machine learning and some knowledge of Kubernetes is required.

By Aniruddha Choudhury

This book gathers recent research work on emerging Artificial Intelligence (AI) methods for processing and storing data generated by cloud-based Internet of Things (IoT) infrastructures. Major topics covered include the analysis and development of AI-powered mechanisms in future IoT applications and architectures.

By Constandinos X. Mavromoustakis, Evangelos Pallis (eds), George Mastorakis, Jordi Mongay Batalla

This book covers the foundations and applications of cloud computing, AI, and Big Data and analyses their convergence for improved development and services.

By Danda B. Rawat, Jitendra Kumar Samriya, Lalit K. Awasthi, Mohit Kumar, Valentina Emilia Balas

This book is a guide to creating AI-driven voice and text agents for customer support and other conversational tasks. This practical and entertaining book combines design theory with techniques for building and training AI systems.

By Andrew Freed

Dive into and apply practical machine learning and dataset categorization techniques while learning Tensorflow and deep learning. This book uses convolutional neural networks to do image recognition all in the familiar and easy to work with Swift language.

By Brett Koonce

Reimagine different generative AI as useful creative prototyping tools that can be used to augment your own creative process and projects. Gain a deeper understanding of how generative AI can elevate your creative future.

By Patrick Parra Pennefather

Giving a new generation access to a classic text, this book lays the theoretical foundations for the multidisciplinary field of cybernetics, the study of controlling the flow of information in systems with feedback loops, be they biological, mechanical, cognitive, or social.

By Doug Hill, Norbert Wiener, Sanjoy K. Mitter

This book teaches you how to successfully deploy state-of-the-art data mesh solutions and gain a comprehensive overview on how a data fabric architecture uses artificial intelligence (AI) and machine learning (ML) for automated metadata management and self-service data discovery and consumption.

By Eberhard Hechler, Maryela Weihrauch, Yan (Catherine) Wu

The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration.

By K. Ramya Laxmi, Kapil Kumar Nagwanshi, Rohit Raja, Sandeep Kumar

Providing a unified reference for specific machine learning solutions to cybersecurity problems, this book supplies a foundation in cybersecurity fundamentals and surveys contemporary challenges detailing cutting-edge machine learning and data mining techniques.

By Sumeet Dua, Xian Du

Teaching readers everything they need to know to get going, this comprehensive resource offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations.

By Christopher J. Pal, Eibe Frank, Ian H. Witten, Mark A. Hall

Offering a thorough grounding in machine learning concepts, this guide provides practical advice on applying machine learning tools and techniques in real-world data mining situations along with tips and techniques for performance improvement.

By Eibe Frank, Ian H. Witten, Mark A. Hall

Discover how to achieve business goals by relying on high-quality, robust data

By Prashanth Southekal

Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling.

By Luiz Paulo Favero, Patricia Belfiore, Rafael de Freitas Souza

This book first summarizes existing evidence of human cognitive mechanism modeling from cognitive psychology and proposes a general framework of deep cognitive networks that jointly considers multiple cognitive mechanisms. Then, it analyzes related works and focuses primarily but not exclusively, on the taxonomy of four key cognitive mechanisms (i.e., attention, memory, reasoning, and decision) surrounding deep cognitive networks.

By Liang Wang, Yan Huang

An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars.

By John D. Kelleher

This book thoroughly explains deep learning models and how to use Python programming to implement them in applications such as NLP, face detection, face recognition, face analysis, and virtual assistance (chatbot, machine translation, etc.).

By Abhishek Kumar, Arwa Mashat, Niha Kamal Basha, Surbhi Bhatia Khan

This book teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI.

By Kevin Ferguson, Max Pumperla

Introducing the pivotal components of deep learning, this book provides you with an in-depth understanding of how to build deep feedforward and convolutional neural networks, as well as variants of denoising autoencoders.

By Robert Blanchard

"Deep Learning for Data Architects" is a comprehensive guide that bridges the gap between data architecture and deep learning. It provides a solid foundation in Python for data science and serves as a launchpad into the world of AI and deep learning.

By Shekhar Khandelwal

Providing real-world examples and hands-on activities to make learning easier, this approachable text gives you the information you need to take the mystery out of the topic-as well as all of the underlying technologies associated with it.

By John Paul Mueller, Luca Massaron

Deep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library.

By Stephan Raaijmakers

Helping you discover the concepts of deep learning used for natural language processing (NLP), this book provides full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models.

By Palash Goyal, Sumit Pandey

Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies.

By Alexandros Iosifidis, Anastasios Tefas

Teaching you how to improve the effectiveness of your search by implementing neural network-based techniques, this book will enable you to build amazing search engines that deliver the results your users need and that get better as time goes on.

By Tommaso Teofili

Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition.

By Mohamed Elgendy

This book provides the reader with the fundamental knowledge in the area of deep learning with application to visual content mining. The authors give a fresh view on Deep learning approaches both from the point of view of image understanding and supervised machine learning.

By Akka Zemmar, Jenny Benois-Pineau

Deep Learning in Personalized Healthcare and Decision Support discusses the potential of deep learning technologies in the healthcare sector. The book covers the application of deep learning tools and techniques in diverse areas of healthcare, such as medical image classification, telemedicine, clinical decision support system, clinical trials, electronic health records, precision medication, Parkinson disease detection, genomics, and drug discovery.

By Harish Garg, Jyotir Moy Chatterjee

Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture focuses on hardware architecture and embedded deep learning, including neural networks.

By Cong Shi, Haijun Liu, Ji Liu, Xichuan Zhou

TinyML, or Tiny Machine Learning, is used to enable machine learning on resource-constrained devices, such as microcontrollers and embedded systems. If you want to leverage these low-cost, low-power but strangely powerful devices, then this book is for you.

By Atul Krishna Gupta, Dr. Siva Prasad Nandyala

Containing real-time deep learning object identification, this book will enable you to design deep learning models and web applications on the Windows operating system.

By Thimira Amaratunga

This book is a deep dive into building successful deep learning applications. You'll save hours of trial-and-error by applying proven patterns and practices to your own projects.

By Andrew Ferlitsch

Teaching you what a pipeline is and how it works so you can build a full application easily and rapidly, this step-by-step book will help you troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models.

By Hisham El-Amir, Mahmoud Hamdy

Exploring deep learning applications using frameworks such as TensorFlow and Keras, this book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications.

By Navin Kumar Manaswi

The ultimate reference for C# .Net developers who are passionate about deep learning, this book provides readers with all the skills necessary to develop powerful, scalable and flexible deep learning models from a fluid and easy to use API.

By Matt R. Cole

Through diverse examples featuring text analysis, speech processing, image recognition, and self-learning game AI, this engaging and easy-to-follow book provides fascinating use cases and in-depth instruction for deep learning apps in JavaScript in your browser or on Node.

By Eric D. Nielsen, Francois Chollet, Shanqing Cai, Stanley Bileschi

For Python programmers with an interest in machine learning, this practical book teaches you to create deep learning and neural network systems with PyTorch and gets you to work right away building a tumor image classifier from scratch.

By Eli Stevens, Luca Antiga, Thomas Viehmann

Filled with practical, relevant applications, this book teaches you how deep learning can augment your existing machine learning and business intelligence systems.

By Mark Ryan

Discover more insight about deep learning algorithms with Swift for TensorFlow. This book covers the deep learning concepts from fundamentals to advanced research.

By Rahul Bhalley

Deep Learning: A Visual Approach is for anyone who wants to understand this fascinating field in depth, but without any of the advanced math and programming usually required to grasp its internals.

By Andrew Glassner

This book delivers the state of the art in deep learning (DL) methods hybridized with evolutionary computation (EC).

By Hitoshi Iba, Nasimul Noman

Teaching you the fundamental concepts and terminology of deep reinforcement learning, this example-rich tutorial will give you the practical skills and techniques you'll need to implement it into your own projects.

By Alexander Zai, Brandon Brown

Gain an in-depth overview of reinforcement learning for autonomous agents in game development with Unity.

By Abhilash Majumder

Using highly intuitive and easy-to-understand examples and applications, this book introduces the cutting-edge research advances that make reinforcement learning capable of out-performing most state-of-art systems, and even humans in a number of applications.

By Mohit Sewak

Guide machine learning projects from design to production with the techniques in this one-of-a-kind project management guide. No ML skills required

By Simon Thompson

In this book, you will learn the root concepts of AI/ML and how these inanimate machines can actually become smarter than the humans at a few tasks, and how companies are using AI and how you can leverage AI to earn profits.

By Prashant Kikani

Build and deploy machine learning and deep learning models in production with end-to-end examples.

By Pramod Singh

Your company has committed to AI. Congratulations, now what? This practical book offers a holistic plan for implementing AI from the perspective of IT and IT operations in the enterprise.

By Eberhard Hechler, Martin Oberhofer, Thomas Schaeck

With a specific focus on software development and AI projects with examples, this book explains the fundamentals of design thinking and how to apply design thinking techniques in defining software development and AI solutions.

By Robert Stackowiak, Tracey Kelly

This book will probe into UX design's role in making technologies inclusive and enabling user collaboration with AI.

By Akshay Kore

Containing real-world examples throughout, this practical book will teach you how to develop bots with zero coding knowledge using the Azure Cognitive QnA Maker service, a GUI cognitive service from Microsoft.

By Kasam Shaikh

Cognitive Virtual Bots are taking the technology and user experience world by storm. This book provides clear guidance on how different cognitive platforms can be used to develop Cognitive Virtual Assistants that enable a conversation by using DialogFlow and advanced NLP.

By Navin Sabharwal, Neha Anand, Pallavi Aggarwal, Sudipta Barua

Looking at the popular paradigms for chatbot construction, this book will provide a comprehensive source of algorithms and architectures for building chatbots for various domains based on the recent trends in computational linguistics and machine learning.

By Boris Galitsky

The book offers a rational insight into technological threats that we will all encounter, and provides navigation in an increasingly technologically advanced world.

By Sarah Katz

Offering example applications and detailed benchmarking experiments with real and synthetic datasets throughout, this book provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field.

By Gustau Camps-Valls, Jordi Muñoz-Marí, José Luis Rojo-Álvarez, Manel Martínez-Ramón

Distributed Machine Learning Patterns provides dozens of techniques for designing and deploying distributed machine learning systems. In it, you'll learn patterns for distributed model training, managing unexpected failures, and dynamic model serving. You'll appreciate the practical examples that accompany each pattern along with a full-scale project that implements distributed model training and inference with autoscaling on Kubernetes.

By Yuan Tang

Providing complete examples with the R programming language and BUGS software, this book begins with the basics, including essential concepts of probability and random sampling, then gradually climbs all the way to advanced hierarchical modeling methods for realistic data.

By John K. Kruschke

This book provides innovative insights into implementing smart systems to detect neurological diseases at a faster rate than by normal means.

By Arindam Bit (eds), Pallab Bhattacharya, Sudip Paul

This book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial.

By Dusit Niyato, Victor C. M. Leung, Xiaofei Wang, Xu Chen, Xueqiang Yan, Yiwen Han

An examination of e-learning, robotics, and tutoring systems, this book provides innovative insights into technology integration methods within classroom settings, including how they can empower students and how they can be used in the creation of dynamic learning experiences.

By Liston W. Bailey

Including innovative research on topics such as deep neural networks, cyber-physical systems, and pattern recognition, this collection of research will benefit individuals such as IT professionals, academicians, students, researchers, and managers.

By Pradeep Kumar Mallick, Samarjeet Borah

In this timely book, the editors explore the current state of practice in Healthcare 4.0 and provide a roadmap for harnessing artificial intelligence, machine learning, and Internet of Things, as well as other modern cognitive technologies, to aid in dealing with the various aspects of an emergency pandemic outbreak.

By Abhinav Juneja, Prashant Tyagi, Sapna Juneja, Vikram Bali, Vishal Jain

Ensemble Methods for Machine Learning teaches you practical techniques for applying multiple ML approaches simultaneously. Each chapter contains a unique case study that demonstrates a fully functional ensemble method, with examples including medical diagnosis, sentiment analysis, handwriting classification, and more.

By Gautam Kunapuli

If you're an industry, business, or technology professional that wants to attain the skills needed to grow your machine learning capabilities and effectively scale the work you're already doing, you'll find what you need in this practical book.

By Rashed Haq

This book targets Machine Learning Engineers, Data Scientists, Data Engineers, Business Intelligence Analysts, and Software Developers who wish to gain a firm grasp on the fundamentals of Deep Learning and Artificial Intelligence. Readers should have a working knowledge of computer programming concepts.

By B N Chandrashekar, Dr. Manjunath Ramachandra, Shashidhar Soppin

This Book features seventeen original essays by prominent AI scientists and philosophers and represents the state-of-the-art thinking in this fast-growing field.

By S. Matthew Liao

Discover one-of-a-kind AI strategies never before seen outside of academic papers! Learn how the principles of evolutionary computation overcome deep learning's common pitfalls and deliver adaptable model upgrades without constant manual adjustment.

By Micheal Lanham

This book presents a range of those efforts, divided into four parts. Part I briefly introduces readers to evolutionary learning and provides some preliminaries.

By Zhou

Experimentation for Engineers: From A/B testing to Bayesian optimization delivers a toolbox of processes for optimizing software systems. You'll start by learning the limits of A/B testing, and then graduate to advanced experimentation strategies that take advantage of machine learning and probabilistic methods.

By David Sweet

Explainable Deep Learning AI: Methods and Challenges presents the latest works of leading researchers in the XAI area, offering an overview of the XAI area, along with several novel technical methods and applications that address explainability challenges for deep learning AI systems.

By Dragutin Petkovic, Georges Quenot, Jenny Benois-Pineau, Romain Bourqui

Learn how to use the large-scale natural language processing model developed by OpenAI: ChatGPT. This book explains how ChatGPT uses machine learning to autonomously generate text based on user input and explores the significant implications for human communication and interaction.

By Eric Sarrion

Providing the knowledge and insight you need to build and maintain your portfolio accordingly, this cutting-edge book describes what to expect, when to expect it, and how to profit in impending technological and economic revolution.

By Jon D. Markman

Presenting key concepts, methods, examples, and applications, this book provides a comprehensive introduction to feature engineering, including feature generation, feature extraction, feature transformation, feature selection, and feature analysis and evaluation.

By Guozhu Dong, Huan Liu (eds)

An essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab, this book presents and explains numerous algorithms to enable complete understanding of the methods and techniques demonstrated.

By Alberto S. Aguado, Mark S. Nixon

Including contributions from leading researchers and practitioners in the field, this thorough resource unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering.

By Ali N. Akansu, Dmitry Malioutov, Sanjeev R. Kulkarni

Providing a comprehensive overview of fog computing technology, this book explores research issues involved in the application of traditional shallow machine learning and deep learning techniques to big data analytics.

By C. S. R. Prabhu

At a time characterized by the steady and vigorous growth of natural language processing, this handbook provides a highly accessible introduction and much-needed reference guide to both the theory and method of NLP.

By Zhiwei Feng

This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts.

By Gerhard Paaß, Sven Giesselbach

Presenting an integrated, real-life case study incorporating all of the related managerial aspects, this book covers all facets of artificial intelligence (AI) and expert systems in a lucid and coherent manner.

By K Sarukesi, P Gopalakrishnan, V S Janakiraman

The book provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications.

By Pradeep Singh

Providing an understanding or the salient features of linear FE analysis, this book begins with the mathematics describing an actual physical problem and continues with the introduction of the FE approximation and the calculation of pertinent arrays and vectors.

By Ioannis Koutromanos

Written in a simple language with a straightforward presentation, this book is a comprehensive work explaining difficult concepts in soft computing, offering a variety of numerical and conceptual problems along with their systematically worked out solutions.

By Kuntal Barua, Prasun Chakrabarti

Featuring numerous hands-on examples throughout, this book teaches you how to build and train your own Generative Adversarial Networks, one of the most important innovations in deep learning.

By Jakub Langr, Vladimir Bok

This book guides you through many AI techniques capable of generating new realities and AI techniques used to generate different forms of content.

By Micheal Lanham

This book will show how generative technology works and the drivers. It will also look at the applications - showing what various startups and large companies are doing in the space. There will also be a look at the challenges and risk factors.

By Tom Taulli

Using real-world examples and reusable code, this book helps you get up to speed on the pros and cons of generic pipeline methodology, and learn to combine shell scripts and Docker to build generic pipelines.

By Brandon Atkinson, Dallas Edwards

This book covers wide areas, including the fundamentals of Machine Learning, Understanding and optimizing Hyperparameters, Convolution Neural Networks (CNN), and Recurrent Neural Networks (RNN).

By Sunil Patel

Getting Started with Natural Language Processing teaches you how to upgrade user-facing applications with text and speech-based features. From the accessible explanations and hands-on examples in this book you'll learn how to apply NLP to sentiment analysis, user profiling, and much more.

By Ekaterina Kochmar

This resource is designed to bridge the gap between theoretical understanding and practical application, making it a useful tool for software developers, data scientists, AI researchers, and tech enthusiasts interested in harnessing the power of GPT-4 in Python environments.

By Oswald Campesato

This book teaches you how to exploit the natural relationships in structured and unstructured datasets using graph-oriented machine learning algorithms and tools. In this authoritative book, you'll master the architectures and design practices of graphs, and avoid common pitfalls. Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks.

By Alessandro Nego

Using illustrations, exercises, and jargon-free explanations to teach fundamental AI concepts, this book explores coding challenges like detecting bank fraud, creating artistic masterpieces, and setting a self-driving car in motion.

By Rishal Hurbans

Grokking Continuous Delivery is a friendly guide to setting up and working with a continuous delivery pipeline. Each chapter takes on a different scenario you'll face when setting up a CD system, with real-world examples like automated scaling and testing legacy applications.

By Christie Wilson

Teaching you to build deep learning neural networks from scratch, this book, written in an engaging style, shows you the science under the hood, so you grok for yourself every detail of training neural networks.

By Andrew W. Trask

Using engaging exercises to teach you how to build deep learning systems, this book combines annotated Python code with intuitive explanations to explore DRL techniques.

By Miguel Morales

This book presents machine learning algorithms and techniques in a way that anyone can understand.

By Luis Serrano

Leverage the power of Artificial Intelligence (AI) to drive the growth and success of your organization. This book thoroughly explores the reasons why it is so hard to implement AI, and highlights the need to reconcile the motivations and goals of two very different groups of people, business-minded and technical-minded.

By Francisco Javier Campos Zabala

Introducing the fundamental concepts of convolutional neural networks (ConvNets), this self-contained guide offers practical guidance on using libraries to implement ConvNets in applications of traffic sign detection and classification.

By Elnaz Jahani Heravi, Hamed Habibi Aghdam

This book will rekindle a passion for deep learning in those already experienced in coding and studying this discipline, and provide a philosophical big-picture perspective for those new to the field.

By Skansi

Hamiltonian Monte Carlo Methods in Machine Learning introduces methods for optimal tuning of HMC parameters, along with an introduction of Shadow and Non-canonical HMC methods with improvements and speedup.

By Rendani Mbuvha, Tshilidzi Marwala, Wilson Tsakane Mongwe

The Handbook of Image Processing and Computer Vision presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding.

By Arcangelo Distante, Cosimo Distante

The Handbook of Image Processing and Computer Vision presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding.

By Arcangelo Distante, Cosimo Distante

This book presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding.

By Arcangelo Distante, Cosimo Distante

Written by expert practitioners from leading companies operating in machine vision, this one-stop handbook guides readers through all aspects of image acquisition and image processing, including optics, electronics and software.

By Alexander Hornberg

Filling the gap between theory and practice, this comprehensive resource provides a set of practical applications for solving problems and applying various techniques in automatic data extraction and setting.

By Sathiyamoorthi Velayutham

The Handbook of Research on Artificial Intelligence in Government Practices and Processes identifies definitional perspectives of behavioral data science and what its use by governments means for automation, predictability, and risks to privacy and free decision making in society.

By Felipe Debasa, Jose Ramon Saura

Highlighting topics such as computer vision, encryption systems, and biometrics, this essential resource presents current trends and the latest research on deep learning and explores the concepts, algorithms, and techniques of data mining and analysis.

By Aboul Ella Hassanien, Ashraf Darwish, Chiranji Lal Chowdhary (eds)

The Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning provides concepts, theories, systems, technologies, and procedures that exhibit properties, phenomena, or abilities of any living system or human.

By Maki K. Habib

The book provides ready-to-use best practices for implementing AIOps in an enterprise. Each component of AIOps and ML using Python code and templates is explained and shows how ML can be used to deliver AIOps use cases for IT operations.

By Gaurav Bhardwaj, Navin Sabharwal

The book covers real projects on TensorFlow, demonstrates how to collect photos with Camera X, and preprocess them with the Google ML Kit. It explains how to onboard the power of machine learning in Android applications that detect images, identify faces, and apply effects to photographs, among other things.

By Vasco Correia Veloso

This book explains about Machine Learning with Python.

By Aditya Joshi, Ashwin Pajankar

Providing step-by-step guidance and in-depth explanations, this book is a good starting point for developers and data scientists who want to create and design NLP systems using BERT.

By Amit Agrawal, Navin Sabharwal

Providing examples in Python that are made specifically for data science, this book combines the Anaconda Python distribution with the popular Scikit-Learn library to demonstrate a wide range of supervised and unsupervised machine learning algorithms.

By David Paper

TinyML is an innovative technology that empowers small and resource-constrained edge devices with the capabilities of machine learning. If you're interested in deploying machine learning models directly on microcontrollers, single board computers, or mobile phones without relying on continuous cloud connectivity, this book is an ideal resource for you.

By Rohan Banerjee

This book represents a valuable resource for students, researchers and practitioners who need to construct face analysis systems with deep generative networks.

By Huaibo Huang, Ran He, Tieniu Tan, Yi Liu

Everything you've always wanted to know about self-driving cars, Netflix recommendations, IBM's Watson, and video game-playing computer programs.

By Sean Gerrish

By breaking down major tech concepts involved with a modern startup into bite-sized chapters, this book peels back the mystery of the Internet, explains it all in the simplest terms, and gives you the knowledge you need to speak confidently when the subject turns to technology.

By Vinay Trivedi

This book introduces the applications of deep learning in various human centric visual analysis tasks, including classical ones like face detection and alignment and some newly rising tasks like fashion clothing parsing.

By Dongyu Zhang, Liang Lin, Ping Luo, Wangmeng Zuo

The book explains how six basic human emotions can be recognized in various face images of the same person, as well as those available from benchmark face image databases like CK+, JAFFE, MMI, and MUG.

By Asit Barman, Paramartha Dutta (eds)

Providing a unique picture of the complete ‘in-the-wild' biometric recognition processing chain, this book covers everything from data acquisition through to detection, segmentation, encoding, and matching reactions against security incidents.

By Hugo Proença, Maria De Marsico, Michele Nappi

Human-Centered Artificial Intelligence: Research and Applications presents current theories, fundamentals, techniques and diverse applications of human-centered AI.

By Chang S. Nam, Jae-Yoon Jung, Sangwon Lee

This book lays out methods for humans and machines to work together effectively. You'll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You'll learn to create training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows.

By Robert (Munro) Monarch

Will the workplace of the future be overrun by machines and robots? Are the new frontiers of artificial intelligence (AI) on the cusp of dethroning us in efficiency, intelligence and innovative potential? Human/Machine is the only guide you need to understand the fourth industrial revolution.

By Daniel Newman, Olivier Blanchard

This book provides an introduction to hyperautomation, highlighting its key components and providing guidance on how organizations can implement it to streamline everyday business operations.

By Dr. Jagreet Kaur, Navdeep Singh Gill, Suryakant

Dive into hyperparameter tuning of machine learning models and focus on what hyperparameters are and how they work. This book discusses different techniques of hyperparameters tuning, from the basics to advanced methods.

By Tanay Agrawal

This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding.

By Jocelyn Chanussot, Saurabh Prasad

This book systematically discusses the basic concepts, theories, research and latest trends in image fusion. It focuses on three image fusion categories - pixel, feature and decision - presenting various applications, such as medical imaging, remote sensing, night vision, robotics and autonomous vehicles.

By Durga Prasad Bavirisetti, Gang Liu, Gang Xiao, Xingchen Zhang

In this book, you'll learn to address this gap in our accounts of how we imagine, conceptualize, design, and use digital technologies.

By Phil Turner

Providing a detailed explanation of the real world and industry wide natural language processing use-cases, this book is for anyone looking to develop the fundamental concepts in NLP and explore more advanced problems.

By Amandeep

Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more.

By Aleksandar Kartelj, Miloš Kotlar, Nenad Mitić, Veljko Milutinović

Putting everything you need to know into one place, this book will show you the step-by-step process for successful implementations of AI, backed up with numerous case studies from top companies.

By Tom Taulli

Showing how machine learning can be applied to address real-world problems in the fourth industrial revolution, this thorough resource provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice.

By Pedro Larrañaga, et al.

Including many advanced, yet practical examples in different industries, this book will help you understand the industrialization of machine learning (ML) and take the first steps toward identifying and generating the transformational disruptors of artificial intelligence (AI).

By Andreas François Vermeulen

Infrastructure as Code, Patterns and Practices teaches flexible techniques for building resilient, scalable infrastructure, including structuring and sharing modules, migrating legacy systems, and more.

By Rosemary Wang

Innovations in Artificial Intelligence and Human Computer Interaction in the Digital Era investigates the interaction and growing interdependency of the HCI and AI fields, which are not usually addressed in traditional approaches.

By Arwa Mashat, Surbhi Bhatia Khan, Suyel Namasudra, Swati Chandna

Innovative Engineering with AI Applications demonstrates how we can innovate in different engineering domains as well as how to make most business problems simpler by applying AI to them.

By Anamika Ahirwar, Bhupesh Gour, Manish Shrivastava, Piyush Kumar Shukla, Priti Maheshwary

Inside Deep Learning illuminates the inner workings of deep learning algorithms in a way that even machine learning novices can understand.

By Edward Raff

This book provides instructions for installation, configuration and troubleshooting sections to improve the IT support productivity and fast resolution of issues that arise.

By Alan Bluck

Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, including compressive sensing and sampling, distributed signal processing, and intelligent signal learning.

By Fei Hu, Qi Hao (eds)

This book contains high-quality research articles and reviews that promote research and reflect the most recent advances in intelligent wavelet based techniques for advanced multimedia applications as well as other emerging areas.

By Amit Kumar Singh, Mohamed Elhoseny (eds), Rajiv Singh, Swati Nigam

Interpretable AI teaches you to identify the patterns your model has learned and why it produces its results. As you read, you'll pick up algorithm-specific approaches, like interpreting regression and generalized additive models, along with tips to improve performance during training.

By Ajay Thampi

Revised to offer an integrated view on evolution-based problem-solving algorithms, this book is suitable for courses in artificial intelligence and computational intelligence, and for self-study by practitioners and researchers engaged with all aspects of bioinspired design and optimization.

By A.E. Eiben, J.E. Smith

A comprehensive textbook on the subject, this book covers a broad array of topics including supervised learning; Bayesian decision theory; parametric, semi-parametric, and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing.

By Ethem Alpaydin

This book will help you evaluate different AI-driven predictive analytics techniques and help you incorporate decision intelligence into your business workflow through real-world examples.

By Adarsha Shivananda, Akshay Kulkarni, Avinash Manure

This book will thoroughly introduce you to ML-Agents in Unity and how to use them in your next project.

By Dylan Engelbrecht

Bringing together cutting-edge technologies that developers need to master in order to compete in today's marketplace, this book demonstrates how complex capabilities can be provided and consumed as a service in the form of easy-to-use APIs, making them more accessible than ever before.

By Anurag Bhandari, Nishith Pathak

This book is designed for those new to Java and interested in understanding how ChatGPT/GPT-4 can enhance programming.

By Oswald Campesato

Delving into several real-life case studies of AI gone wrong, this book explores the inherent risk factors of the widespread implementation of artificial intelligence and addresses the need to challenge our current assumptions about the infallibility of technology.

By Anand Tamboli

Introducing the topics of Machine Learning (ML) and Deep Learning (DL) from a practical perspective, this book takes you through real-world examples of building DL models in Keras for recognizing product logos in images and extracting sentiment from text.

By Dattaraj Jagdish Rao

Unlock the full capabilities of ChatGPT at work, at home, and in your day-to-day

By Guy Hart-Davis

Written for anyone in a leadership or management role-from C-level/unit team managers to rising talent-this powerful, hands-on guide meets today's growing need for real-world tools to lead and succeed with data.

By Eric Anderson, Florian Zettelmeyer

Showing you how to combine the power of AI and LSS to seize competitive advantage, this game-changing guide takes you through the process of using AI to dramatically enhance any LSS management program.

By Daniel K. Blackwell, Dinesh Rajan, Michael George, Michael George Jr.

This book is for anyone interested in learning about artificial intelligence and putting it into practice with Python. This book is also valuable for intermediate Machine Learning practitioners as a reference guide. Readers should be familiar with the fundamental understanding of Python programming and machine learning techniques.

By Gaurav Leekha

Writing computer programs in Python just got a lot easier! Use AI-assisted coding tools like GitHub Copilot and ChatGPT to turn your ideas into applications faster than ever.

By Daniel Zingaro, Leo Porter

Teaching you how to build practical applications of computer vision using the OpenCV library with Python, this book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples.

By Sunila Gollapudi

With practical business-centric use-cases implemented in Keras, this concise resource provides you with a thorough understanding of deep learning principles and practical hands-on experience in developing enterprise-grade deep learning solutions in Keras.

By Jojo Moolayil

Introducing readers to the latest version of the TensorFlow library, this book will teach you how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples.

By Avinash Manure, Pramod Singh

Machine and Deep Learning Using MATLAB is a useful and highly comprehensive resource on the subject for professionals, advanced students, and researchers who have some familiarity with MATLAB and are situated in engineering and scientific fields, who wish to gain mastery over the software and its numerous applications.

By Kamal I. M. Al-Malah

This book offers the first systematic guide to machine ethics, bridging between computer science, social sciences and philosophy.

By Luís Moniz Pereira

Machine Intelligence, Big Data Analytics, and IoT in Image Processing is a significant addition to the body of knowledge on practical applications emerging from machine intelligence, big data analytics, and IoT. The chapters deal with specific areas of applications of these technologies.

By Ashok Kumar, Jose A. Galindo, Lalit Garg, Megha Bhushan, Yu-Chen Hu

Exploring the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare, this book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges.

By Arjun Panesar

Offering a guided tour of machine learning algorithms and architecture design, this book provides real-world applications of intelligent systems in healthcare and covers the challenges of managing big data.

By Arjun Panesar

This book is intended to present the state of the art in research on machine learning and big data analytics.

By Aboul Ella Hassanien, Ashraf Darwish

Including hands-on tools and numerous case studies, this book aims to provide awareness of algorithms used for machine learning and big data in the academic and professional community.

By Khairol Amali Bin Ahmad, Khaleel Ahmad, Uma N. Dulhare

Including case studies on business and AI, this book discusses the emergence and evolution of IT in the enterprise, how machine learning is transforming business intelligence, and the various cognitive artificial intelligence solutions that complement and extend machine learning.

By Rohit Kumar

Featuring self-contained chapters with a thorough literature review, this thorough reference demonstrates the application of cutting-edge machine learning techniques to medical imaging problems.

By Dinggang Shen, Guorong Wu, Mert R. Sabuncu (eds)

Providing an overview of machine learning, this text summarizes the state-of-the-practice in this niche area, gives a classification of the existing work, and offers application guidelines.

By Du Zhang, Jeffrey J.P. Tsai (eds)

Gain practical skills in machine learning for finance, healthcare, and retail.

By Puneet Mathur

This book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications.

By Jyotir Moy Chatterjee, Monika Mangla, Sachi Nandan Mohanty, Sirisha Potluri, Suneeta Satpathy

This book deeply discusses two of the most critical emerging fields of machine learning: blockchain technology and the Internet of Things

By Akansha Singh, Krishna Kant Singh, Sanjay K. Sharma

This book introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts.

By Athira P. Vijayaraghavan, Sabu Emmanuel, Tony Thomas

This book presents realistic, practical machine learning scenarios, along with crystal-clear coverage of key concepts. In it, you'll complete engaging projects, such as creating a car price predictor using linear regression and deploying a churn prediction service.

By Alexey Grigorev

Providing common machine learning and Python keywords and definitions to make learning even easier, this book show you how to create, execute, modify, and share machine learning applications with Python and TensorFlow 2.0 in the Jupyter Notebook environment.

By Nikita Silaparasetty

This book systematically introduces the competitions in the field of algorithm and machine learning. The first author of the book has won 5 championships and 5 runner-ups in domestic and international algorithm competitions.

By Peng Liu, Qian Qian, Wang He

This cookbook is meant for anybody who is passionate enough to get into the World of Machine Learning and has a preliminary understanding of the Basics of Linear Algebra, Calculus, Probability, and Statistics. This book also serves as a reference guidebook for intermediate Machine Learning practitioners.

By Rehan Guha

An Introduction to the Machine Learning Empowered Intelligent Data Center Networking

By Bo Li, Mingsong Chen, Shui Yu, Ting Wang

Machine Learning Engineering in Action teaches you core principles and practices for designing, building, and delivering successful machine learning projects.

By Ben Wilson

The book helps you achieve the objectives of safeguarding the confidentiality, integrity, and availability of your organizational assets.

By Maris Sekar

The second edition of "Machine Learning for Beginners" addresses key concepts and subjects in machine learning.

By Dr. Harsh Bhasin

This book covers important concepts and topics in Machine Learning. It begins with Data Cleansing and presents an overview of Feature Selection. It then talks about training and testing, cross-validation, and Feature Selection.

By Harsh Bhasin

Machine Learning for Biometrics: Concepts, Algorithms and Applications highlights the fundamental concepts of machine learning, processing and analyzing data from biometrics and provides a review of intelligent and cognitive learning tools which can be adopted in this direction.

By Banshidhar Majhi, Bhabani Shankar Prasad Mishra, Madhumita Panda, Partha Pratim Sarangi, Subhashree Mishra

Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro(r), 2nd ed. offers an accessible and engaging introduction to machine learning. It provides concrete examples and case studies to educate new users and deepen existing users' understanding of their data and their business.

By Galit Shmueli, Mia L. Stephens, Muralidhara Anandamurthy, Nitin R. Patel, Peter C. Bruce

Concentrating on practical topics like customer retention, forecasting, and back office processes, this practical book teaches business-oriented machine learning techniques you can do yourself.

By Doug Hudgeon, Richard Nichol