This is my self-study path to become a Data Scientist.
Content on Stock Market, Backtesting tools, Quantitative Research, Strategies and Analysis.
Favorite books, key lessons and notes on them
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Posts by Category
- backtesting (2)
- behavioral books (3)
- books (8)
- data science books (2)
- data scientist (2)
- trading books (3)
All posts
- Data Science Foundation Self-Study Guide
- Key Lessons on “Mind Over Markets: Power Trading with Market Generated Information” by James F. Dalton, Eric T. Jones, Robert B. Dalton
- Key Lessons on Market Wizards Books by Jack Schwager
- Key Lessons on “Atomic Habits: An Easy & Proven Way to Build Good Habits & Break Bad Ones” by James Clear
- Key lessons on “How We Decide” by Jonah Lehrer
- Self-Study guide to become a Data Scientist
- Key Lessons on “Feature Engineering and Selection: A Practical Approach for Predictive Models” by Max Kuhn and Kjell Johnson
- Key lessons on “Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists” by Alice Zheng, Amanda Casari
- Key Lessons on “One Good Trade: Inside the Highly Competitive World of Proprietary Trading” by Mike Bellafiore
- Key Lessons on “Thinking in Bets: Making Smarter Decisions When You Don’t Have All the Facts” by Annie Duke
- QStrader simulation engine customizations
- Backtest Framework with Python