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Deep.Learning.Vol.1.From.Basics.to.Practice.2018

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Table of Contents Chapter 1 Introduction To Machine Learning Chapter 2 Statistics Chapter 3 Probability Chapter 4 Bayes' Rule Chapter 5 Curves And Surfaces Chapter 6 Information Theory Chapter 7 Classification Chapter 8 Training And Testing Chapter 9 Overfitting And Underfitting Chapter 10 Neurons Chapter 11 Learning And Reasoning Chapter 12 Data Preparation Chapter 13 Classifiers Chapter 14 Ensembles Chapter 15 Scikit-Learn Chapter 16 Feed Forward Networks Chapter 17 Activation Functions Chapter 18 Backpropagation Chapter 19 Optimizers
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