Machine Learning using Python

Tongue: English
Leaves: 366
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book is written to provide a strong foundation in Machine Learning using Python libraries by providing real-life case studies and examples. It covers topics such as Foundations of Machine Learning, Introduction to Python, Descriptive Analytics and Predictive Analytics. Advanced Machine Learning concepts such as decision tree learning, random forest, boosting, recommender systems, and text analytics are covered. The book takes a balanced approach between theoretical understanding and practical applications. All the topics include real-world examples and provide step-by-step approach on how to explore, build, evaluate, and optimize machine learning models.

✦ Table of Contents

Page 1......Page 1
Page 1......Page 2
Page 2......Page 3
Page 3......Page 4
Page 4......Page 5
FM......Page 6
Chapter 01_Introduction to Machine Learning......Page 22
Chapter 02_Descriptive Analytics Exploring and Preparing Datasets......Page 50
Chapter 03_Probability Distributions and Hypothesis Tests......Page 84
Chapter 04_Linear Regression......Page 116
Chapter 05_Classification......Page 156
Chapter 06_Advanced Machine Learning......Page 200
Chapter 07_Clustering......Page 266
Chapter 08_Forecasting......Page 284
Chapter 09_Recommender Systems......Page 312
Chapter 10_Text Analytics......Page 338
Index......Page 360
Page 1......Page 366

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