Advanced Algorithm

Please read Deep learning by Yoshua Bengio Ian Goodfellow ,Aaron Courvill ,chapters 3

and write a summary report

3 Probability and Information Theory 3.1 Why Probability? 3.2 Random Variables 3.3 Probability Distributions. 3.4 Marginal Probability 3.5 Conditional Probability 46 46 48 49 51 51 CONTENTS 3.6 The Chain Rule of Conditional Probabilities. 3.7 Independence and Conditional Independence 3.8 Expectation, Variance, and Covariance 3.9 Information Theory.. 3.10 Common Probability Distributions 3.11 Useful Properties of Common Functions 3.12 Bayes' Rule ... 3.13 Technical Details of Continuous Variables 3.14 Structured Probabilistic Models 3.15 Example: Naive Bayes.. 52 52 53 54 57 62 64 64 65 68