mlfinlab

What it is

A Python library implementing techniques from Marcos Lopez de Prado's "Advances in Financial Machine Learning", covering the full machine learning strategy pipeline from financial data structures and feature engineering to labeling, cross-validation, bet sizing, and backtest statistics. Quantitative researchers can draw on modules for sampling, clustering, hyper-parameter tuning, feature importance, synthetic data generation, and measures of codependence, supported by documentation, example notebooks, and lecture videos. The library is well suited to practitioners building machine learning strategies who want tested implementations of academic methods. Access is governed by an all-rights-reserved licence, so it is not open source despite appearing in a public repository, and community support is tied to paid licensing options.