Shypd.aiThe largest open index of AI toolsAFML provides answers and experimental solutions for exercises from the book 'Advances in Financial Machine Learning' by Dr. Marcos López de Prado. It helps users understand and implement quantitative strategies in financial machine learning.
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AFML is an open-source GitHub repository offering experimental answers and solutions to exercises found in 'Advances in Financial Machine Learning' by Dr. Marcos López de Prado. This resource is invaluable for individuals seeking to develop a solid understanding of quantitative strategies and their implementation. The repository includes Python notebooks covering various chapters and concepts from the book, such as triple barriers and bet sizing, which are applicable across different strategy types like volatility and trends. While the original book's code was in Python 2.7, AFML provides updated solutions compatible with modern Python versions and libraries. It serves as a reference for those who wish to write their own code from scratch, offering guidance and explanations for complex financial machine learning concepts.
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