Books

1. CS

1. Mining of Massive Datasets (chapter 3, 9)

2. Reinforcement Learning: An Introduction by Richard Sutton and Andrew Barto (Full) notes1, notes2

2. Maths

1. Optimal Transport: Old and New (part 1)

2. Computational Optimal Transport (Full)

3. Statistics

1. MIT notes on High Dimensional Stat (Full)

2. Element of Statistical Learning (chapter 1-3)

3. An Introduction to Probabilistic Graphical Models (chapter 1-4, 8, 11)

4. Bayesian Data Analysis (chapter 10-12)

5. Counterfactuals and Causal Inference (chapter 1-7)

6. Theoretical Statistics: Topics for a Core Course (Full)

7. All of Non-parametric Statistics (Full)

8. Lecture Notes for Statistics 311/Electrical Engineering 377 - John Duchi (Full)

4. Finance

1. The Element of Financial Econometrics) (Full)
2. Advances in Financial Machine Learning (Full)
3. Econometrics of Financial High-Frequency Data by Nikolaus Hautsch (chapter 1-3,5,8-9)
4. Empirical market microstructure: The institutions, economics, and econometrics of securities trading (Full)
5. Market Microstructure in Practice (Full)
6. Active Equity Management