Machine learning system learning book knowledge - two chapters a week, are listed below:
1. Model evaluation and selection
Linear model
2. Decision Tree
Neural Networks
3. Support Vector Machine
Bayesian classifier
4. Integrated Learning
Clustering
The measure learning and dimensionality reduction
Feature selection and sparse learning
6. Calculate Learning Theory
Semi-supervised learning
7. probabilistic graphical models
Rule learning
8. Reinforcement Learning