Sentiment Analysis and Recommender Systems with Python Bootcamp

  • 3 Books | 17h 51m
  • Includes Lab
Welcome to the Sentiment Analysis and Recommender Systems with Python Bootcamp. This program will give students the foundational skills they need in order to process, clean, and format text data for analysis, build predictive machine learning models as well as build and evaluate recommender systems based on real data. Prerequisites: Attendees must be comfortable using Python to manipulate data and must know how to create advanced visualizations in Python. Additionally, students must have a foundation in classification techniques. Objectives: Program proficiently in Python Clean, process, and visualize text data Develop a framework for analyzing data to improve processes and accuracy Identify and define use cases for recommender systems Build and evaluate content-based recommender systems Build and evaluate item-based filtering algorithm


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Machine Learning with PySpark: With Natural Language Processing and Recommender Systems
Including numerous case studies and examples throughout, this book will teach you how to build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business challenges.
Book Duration 1h 50m Book Authors By Pramod Singh


Practial Recommender Systems
This book explains how recommender systems work and shows how to create and apply them for your site.
Book Duration 6h 55m Book Authors By Kim Falk


Python: An Introduction to Programming, Second Edition
In this Book you will learn the fundamentals of programming, the text assumes no programming experience.
Book Duration 9h 6m Book Authors By James R. Parker