BlackArbsCEO/Adv_Fin_ML_Exercises resource

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1954 stars · 657 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of experimental Jupyter notebook solutions to selected exercises from the book 'Advances in Financial Machine Learning' by Marcos Lopez De Prado. It includes reusable Python source modules like bars.py and snippets.py for financial ML techniques.

Use cases

• solving exercises from Advances in Financial Machine Learning
• learning financial machine learning techniques
• implementing information-driven bars like dollar and volume bars
• studying sample weighting and cross-validation for financial data
• exploring quant trading ML workflows in Python

When to choose

• you are reading the AFML book and want worked exercise solutions
• you want Python reference implementations of financial ML concepts
• you are a quant learning ML applied to market data

When to avoid

• you need production-ready, tested financial ML libraries
• you want a maintained framework with active development
• you need guaranteed correctness of solutions

Facets

learning-resource · maturity maintenance

machine-learning data-science trading fintech machine-learning tutorials python cross-platform jupyter-notebooks quantitative-finance financial-machine-learning book-exercises education

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