Books for Machine Learning, Deep Learning, and related topics

1. Machine Leaning and Deep Learning

1. A First Course in Machine Learning-2012.pdf
2. AutoML Machine Learning-Methods, Systems, Challenges-2018.pdf
3. Building Machine Learning Systems with Python-2nd Edition-2015.pdf
4. Data Mining, Inference, and Prediction-2017.pdf
5. Data Science from Scratch- First Principles with Python-2015.pdf
6. Deep Learning with Keras-2017.pdf
7. Deep Learning with Python A Hands-on Introduction-2017.pdf
8. Deep Learning With Python-Develop Deep Learning Models on Theano and TensorFlow Using Keras-2017.pdf
9. Deep Learning with Python-Francois_Chollet-En-2018.pdf
10. Deep Learning with Python-Francois_Chollet-中文-Python深度学习-2018.pdf
11. Deep Learning with Tensorflow-2017.pdf
12. Deep Learning-EPFL EE559-2019
13. Deep Learning-Josh Patterson & Adam Gibson-2017.pdf
14. Deep_Learning-Ian_Goodfellow-En-2016.pdf
15. Deep_Learning-Ian_Goodfellow-中文-2017.pdf
16. Deep_Learning-台大李宏毅-En-2016.pdf
17. Designing Machine Learning Systems with Python-2016.pdf
18. Elements of Statistical Learning-2017.pdf
19. Foundations of Data Science-2018.pdf
20. Fundamentals of Deep Learning-2017.pdf
21. Gaussian Processes for Machine Learning-2006.pdf
22. Hands on Machine Learning with Scikit Learn and TensorFlow-En-2017.pdf
23. Hands on Machine Learning with Scikit Learn and TensorFlow-中文-机器学习实用指南-2017.pdf
24. Hands on Machine Learning with Scikit Learn Keras and TensorFlow 2nd Edition-2019.pdf
25. Introduction to Machine Learning with Python-2016.pdf
26. Introduction to Machine Learning-sencond-edition-EN-2010.pdf
27. Learning Generative Adversarial Networks-2017.pdf
28. Learning TensorFlow-2017.pdf
29. Machine Learning for OpenCV-2017.pdf
30. Machine Learning in Action-EN-2012.pdf
31. Machine Learning in Action-中文-2012.pdf
32. Machine Learning in Python-2015.pdf
33. Machine Learning with Python Scikit-Learn-2015.pdf
34. Machine Learning Yearning-Andrew Ng-2018.pdf
35. Machine Learning-A Probabilistic Perspective-2012.pdf
36. Mastering Feature Engineering-2016.pdf
37. Mastering Machine Learning with scikit-learn-2017.pdf
38. MATLAB Machine Learning by Michael Paluszek-2017.pdf
39. Pattern Recognition And Machine Learning _中文-马春鹏-2014.pdf
40. Pattern Recognition And Machine Learning-EN-2006.pdf
41. Practical Machine Learning with H2O-2016.pdf
42. Practical Machine Learning-A New Look at Anomaly Detection-2014.pdf
43. Pro Deep Learning with TensorFlow-2017.pdf
44. Python Machine Learning-2015.pdf
45. Python Real World Machine Learning - Prateek Joshi-2016.pdf
46. Tensorflow for Deep Learning Research-Stanford CS 20-2018
47. Tensorflow Machine Learning Cookbook-2017.pdf
48. Tensorflow实战Google深度学习框架-2017.pdf
49. 机器学习(西瓜书)_周志华-中文-2016.pdf
50. 深度学习入门之PyTorch-2017.pdf

2. Python Books

1. Learn Python The Hard Way 3rd Edition-2014.pdf
2. Learning PySpark-2017.pdf
3. Python Data Analytics-2015.pdf
4. SciPy and NumPy-2012.pdf
5. Scipy Lecture Notes-2015.pdf
6. Understanding GIL-2010.pdf

3. Math Books

1. An introduction to optimization-4th-edition-2013.pdf
2. Convex Optimization-2009.pdf
3. Introduction to Applied Linear Algebra-2018.pdf
4. Introduction to Linear Algebra-5th edition-2016.pdf
5. Mathematics and Computation-2018.pdf
6. Mathematics for Machine Learnin-2017.pdf
7. Mathematics for machine learning-2017.pdf
8. Mathematics for Machine Learning-2019
9. MIT18_657_Mathematics of Machine Learning-2015.pdf
10. The Matrix Cookbook-2012.pdf
11. 凸优化-中文版-2013.pdf
12. 数学分析教程-常庚哲_史济怀-上册-2003.pdf
13. 数学分析教程-常庚哲_史济怀-下册-2003.pdf
14. 最优化导论-第四版-2015.pdf
15. 贝叶斯网引论-张连文-2006.pdf
16. 高等代数学习指导书.丘维声.上册-2005.pdf
17. 高等代数学习指导书.丘维声·下册-2009.pdf
18. 高等代数（上）丘维声-2010.pdf
19. 高等代数（下）丘维声-2010.pdf

4. NLP Books

1. Applied Text Analysis with Python-2016.pdf
2. Natural Language Processing with Python-2009.pdf
3. Natural Language Processing with Python.pdf
4. Natural Language Processing-2018.pdf
5. Natural Language Understanding with Distributed Representation-2017.pdf
6. Neural Transfer Learning for Natural Language Processing-Sebastian Ruder-2019.pdf
7. NLTK Essentials-2015.pdf
8. oxford-cs-deepnlp-2017
9. Text Analytics with Python A Practical Real-World Approach to Gaining Actionable Insights from your Data-2016.pdf
10. The Text Mining HandBook-2007.pdf
11. 自然语言处理综论-2005.pdf

5. Computer Vision (CV) Book

1. Learning Image Processing with OpenCV-2015.pdf

6. Reinforcement Learning Books

1. An Introduction to Deep Reinforcement Learning-2018.pdf
2. Dissecting Reinforcement Learning-2016
3. Reinforce Learning-An introduction, 2nd edition-2018.pdf

7. Speech Processing

1. Automatic Speech Recognition-解析深度学习语音识别实践-中文-2016.pdf
2. Automatic Speech Recognition_A Deep Learning Approach-2015.pdf
3. Spoken Language Processing-2001.pdf
4. 离散时间信号处理_第3版_中文-2015.pdf
5. 离散时间语音信号处理：原理与应用-中文-2004.pdf

cheatsheets

1. bokeh-cheatsheet.pdf
2. cheatsheet-deep-learning.pdf
3. cheatsheet-machine-learning-tips-and-tricks.pdf
4. cheatsheet-supervised-learning.pdf
5. cheatsheet-unsupervised-learning.pdf
6. keras-cheatsheet.pdf
7. linearAlgebra-cheatsheet.pdf
8. matplotlib-cheatsheet.pdf
9. notebook-cheatsheet.pdf
10. numpy-cheatsheet.pdf
11. pandas-cheatsheet.pdf
12. refresher-algebra-calculus.pdf
13. refresher-probabilities-statistics.pdf
14. super-cheatsheet-machine-learning.pdf