ML_readme.md

Machine Learning Lecture

1. 线性回归
2. 逻辑回归
3. 正则化
4. 神经网络
5. 神经网络2
6. 应用建议
7. 系统设计
8. SVM
9. K-m, PCA
10. 异常检测
11. 推荐系统
12. 随机梯度下降
13. 照片光学字符识别

Octave Tutorial

1. 矩阵操作
2. plot data
3. 流程控制/方法

CS188 AI

• Search

1. 1~3 Search
2. 4~5 CSP
3. 6~7 AdversarialSearch
4. 8~9 MDP
5. 10-11 Reinforcement Learning

• Inferrence

6. 12 Probability
7. 16 BNs Representation
8. 17 BNs Independence
9. 18 BNs Inference
10. 19 BNs Sampleing
11. 20 Decision Diagram
12. 13 Markov Models
13. 14 HMM
14. 14.5 Particle Filtering
15. 15 Application of HMM

• Machine Learning

20. 20 MK: Naive Bayes
21. 21 Perceptrons and Logistic Regression
22. 22 Optimiaztion and Neural Nets
23. 23 DecisionTrees
24. 24 Application

TensorFlow2

• Intro2 TensorFlow 2

Others

2. OpenAI GYM
3. RL David Silver 随笔
4. RL David Silver 随笔
5. Neural Network Coursera
6. DeepLearning MIT 6S191
7. MAXQ-Q
8. RL,art of state
9. 台大 机器学习基石
10. how alphazero works
11. 梯度下降推导
12. Inferring DQN structure

Old article

1. scipy 统计和随机数
2. scipy 稀疏矩阵
3. scipy 图像处理
4. sklean机器学习
5. sklearn 随机森林简单介绍