Notes for Machine Learning

Most of the materials come from Machine Learning written by Kevin Murphy, An Introduction to Statistical Learning, The Elements of Statistical Learning written by Robert Tibshirani and Trevor Hastie, Introduction to Operation Research, Deep Learning.

Contents:

• Chapter 2: Statistical Learning
• Chapter 3: Linear Regression
• Chapter 4: Classifications
• Chapter 5: Resampling Methods
• Chapter 6: Model Selection and Regularization
• Chapter 11: Neural Network
• Optimization: Non-Linear Programming

TODO:

• Chapter 11: Neural Network
  1. Computational graph
  2. Batch Normalization derivative in computational graph
• Nonlinear Programming
  1. The Gradient Search Procedure