It provides a Python toolbox for quantitative analysts and traders to apply machine learning across the entire financial strategy development pipeline.
MlFinLab offers a Python library for financial machine learning, assisting with tasks from data structuring and feature engineering to model building and backtest analysis. It includes modules for `Labeling`, `Sampling`, `Cross-Validation`, `Feature Importance`, and `Bet Sizing`. You'll find extensive documentation, example notebooks, and lecture videos to guide you through its use.
It provides a Python toolbox for quantitative analysts and traders to apply machine learning across the entire financial strategy development pipeline.
Quantitative analysts, portfolio managers, and financial researchers interested in applying machine learning to trading and investment strategies should use this.