Machine learning (ML) and deep learning (DL)
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Books
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### ML


- [An Introduction to Statistical Learning. Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani](https://www-bcf.usc.edu/~gareth/ISL/ISLR%20First%20Printing.pdf) 
  
### DL

- [Deep Learning](https://www.deeplearningbook.org/) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
- [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com/) 
  by [Michael Nielsen](https://twitter.com/michael_nielsen)

### Slightly overcomplicated

- [Foundations of Data Science](https://www.microsoft.com/en-us/research/publication/foundations-of-data-science/)
- [Understanding Machine Learning: From Theory to Algorithms](https://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/copy.html)


Courses
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### ML

- [ods](https://github.com/Yorko/mlcourse.ai)
- [Andrew Ng course](https://www.coursera.org/learn/machine-learning)
- [QuantEcon ML application](https://datascience.quantecon.org/applications/)

  
### DL

- [fast.ai](https://www.fast.ai/) 
- [deeplearning.ai](https://www.deeplearning.ai/deep-learning-specialization)


Weak link
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- [Puzzles of modern machine learning by Boaz Barak](https://windowsontheory.org/2019/11/15/puzzles-of-modern-machine-learning/)