Machine Learning

The course material for Machine Learning.

The lab material

1. Lab Introduction
2. Preliminary
3. Naïve-Bayes
4. Linear Regression
5. Decision Tree & Random Forest
6. Multilayer Perceptron (MLP)
7. Convolutional Neural Network
8. Detection and tracking *
9. SVM
10. K-mean
11. EM clustering
12. Hidden Markov Model
13. Grape Model *
14. Markov Decision Process (MDP)
15. Reinforcement Learning *
16. Final Project

Authors

• Jia Yanhong