Some resouces for getting started with data science and quant.
Statistics & Regression:
- Wooldridge - Introductory Econometrics
- Hastie - Elements of Statistical Learning
- Shumway - Time Series Analysis and Its Applications
- Yamane - Statistics for Economists, Courses
- Lambert - A graduate course in econometrics
- Cunningham - Causal Inference: The Mixtape
- Taboga - Statlect
Math
- Peter - Mathematics for Machine Learning
- Petersen - Matrix Cookbook
- Boyd - Convex Optimization
- Russell - Artificial Intelligence: A Modern Approach
- Silver - DeepMind x UCL | Introduction to Reinforcement Learning
- AWS - MLU-Explain
Competitive Programming
- Laaksonen - Competitive Programmer’s Handbook
- Qi - USACO Guide
- Kogler - Algorithms for Competitive Programming
- Problem Banks: CodeForces, AtCoder, Project Euler, Kattis, CodinGame, Grind75
Brainteaser Collections:
- Zhou - A Practical Guide To Quantitative Finance Interviews
- Crack - Heard on The Street
- Mosteller - Fifty Challenging Problems in Probability
- Winkler - Mathematical Puzzles
- Mathai - An Introduction to Geometrical Probability
- Lehoczky - The Art of Problem Solving
- Some internships to apply for
Quant:
- Bali - Empirical Asset Pricing
- Dama - On Automated Trading
- Mudders are invited to join Harvey Mudd Data Science
Fun Reads:
- AoPS - Broken Stick variations
- Wildenhain - Microsoft Word is Turing Complete
- Murphy - GradIEEEnt Half Decent
- Kranakis - An interesting queuing problem
- Marx - Calculus