Fundamentals of Machine Learning for Predictive Data Analytics, 2e

| ISBN: 9780262364911 | Copyright 2020

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Preface (pg. xv)
Notation (pg. xxiii)
List of Figures (pg. xxxi)
List of Tables (pg. xlvii)
I Introduction to Machine Learning and Data Analytics (pg. 1)
1 Machine Learning for Predictive Data Analytics (pg. 3)
2 Data to Insights to Decisions (pg. 23)
3 Data Exploration (pg. 53)
II Predictive Data Analytics (pg. 115)
4 Information-Based Learning (pg. 117)
5 Similarity-Based Learning (pg. 181)
6 Probability-Based Learning (pg. 243)
7 Error-Based Learning (pg. 311)
8 Deep Learning (pg. 381)
9 Evaluation (pg. 533)
III Beyond Prediction (pg. 595)
10 Beyond Prediction: Unsupervised Learning (pg. 597)
11 Beyond Prediction: Reinforcement Learning (pg. 637)
IV Case Studies and Conclusions (pg. 683)
12 Case Study: Customer Churn (pg. 685)
13 Case Study: Galaxy Classification (pg. 703)
14 The Art of Machine Learning for Predictive Data Analytics (pg. 729)
V Appendices (pg. 743)
A Descriptive Statistics and Data Visualization for Machine Learning (pg. 745)
B Introduction to Probability for Machine Learning (pg. 757)
C Differentiation Techniques for Machine Learning (pg. 765)
D Introduction to Linear Algebra (pg. 771)
Bilbiography (pg. 775)
Index (pg. 787)
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