Handbook of Research on Applications and Implementations of Machine Learning Techniques

  • 9h 37m
  • Sathiyamoorthi Velayutham
  • IGI Global
  • 2020

The machine learning approach provides a useful tool when the amount of data is very large and a model is not available to explain the generation and relation of the data set.

The Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques provides a set of practical applications for solving problems and applying various techniques in automatic data extraction and setting. A defining collection of field advancements, this Handbook of Research fills the gap between theory and practice, providing a strong reference for academicians, researchers, and practitioners.

In this Book

  • Analysis of Machine Learning Algorithms for Breast Cancer Detection
  • Cognitive-Based Cover Image Selection in Image Steganography
  • Disease Identification in Plant Leaf Using Deep Convolutional Neural Networks
  • Genetically-Modified K-Medoid Clustering Algorithm for Heterogeneous Data Set
  • Implementation of Deep Learning Neural Network for Retinal Images
  • Intensity Inhomogeneity Correction in Brain MR Images Based on Filtering Method
  • Machine Learning and Its Use in E-Commerce and E-Business
  • Machine Learning in Python: Diabetes Prediction Using Machine Learning
  • Medical Reports Analysis Using Natural Language Processing for Disease Classification
  • Optimization of Evolutionary Algorithm Using Machine Learning Techniques for Pattern Mining in Transactional Database
  • Prediction of High-Risk Factors in Surgical Operations Using Machine Learning Techniques
  • Privacy Preserving Machine Learning and Deep Learning Techniques: Application – E-Healthcare
  • Trend and Predictive Analytics of Dengue Prevalence in Administrative Region
  • Relative Analysis on Algorithms and Applications of Deep Learning
  • Application of Machine Learning Techniques in Healthcare
  • Contribution of Neural Networks in Different Applications
  • Introducing the Deep Learning for Digital Age
  • Introduction to Machine Learning and Its Implementation Techniques
  • Introduction to the World of Artificial Intelligence
  • Machine Learning Techniques Application: Social Media, Agriculture, and Scheduling in Distributed Systems
  • Programming Language Support for Implementing Machine Learning Algorithms
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