notes about machine learning

很喜欢一句话：应用之道，存乎一心，与大家共勉

ps：如果我的笔记对你有帮助，给个star叭！查看机器学习笔记的PDF订阅版(301页)以及更多计算机相关笔记，欢迎大家关注微信公众号"Sakura的知识库"~

ML配套Assignments (ppt+code)：https://github.com/Sakura-gh/ML-assignments

内容包括：Regression, Classification, CNN, RNN, Explainable AI, Adversarial Attack, Network Compression, Seq2Seq, GAN, Transfer Learning, Meta Learning, Life-long Learning, Reforcement Learning.

the github page is: https://Sakura-gh.github.io/ML-notes

you can also visit gitee page for quicker Internet in China: https://Sakura-gh.gitee.io/ml-notes

1_Introduction

2_Regression Case Study

3_Regression demo(Adagrad)

4_Where does the error come from

5_Gradient Descent

6_Classification

7_Logistic Regression

8_Deep Learning

9_Backpropagation

10_Keras

11_Convolutional Neural Network part1

12_Convolutional Neural Network part2

13_Tips for Deep Learning

14_Why Deep

15_Semi-supervised Learning

16_Unsupervised Learning Introduction

17_Unsupervised Learning PCA part1

18_Unsupervised Learning PCA part2

19_Matrix Factorization

20_Unsupervised Learning Word Embedding

21_Unsupervised Learning Neighbor Em