stefan-jansen/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
Jupyter Notebook21K stars5.6K forks+82 today
Topics
#machine-learning#trading#investment#finance#data-science#investment-strategies#artificial-intelligence#trading-strategies#deep-learning#synthetic-data#ml4t-workflow#trading-agent#algorithmic-trading#backtesting#large-language-models#polars#quantitative-finance#reinforcement-learning
What it does
This repository provides extensive Jupyter notebooks and code examples for the book 'Machine Learning for Algorithmic Trading', demonstrating practical applications of ML techniques in trading strategies. It is valuable for anyone interested in applying machine learning to financial markets.
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Tracking
- Last trending
- 2026-06-01
Creator kit
Hook
Dive into the world of ML-driven trading strategies with over 150 Jupyter notebooks and detailed explanations from 'Machine Learning for Algorithmic Trading'. #MLforTrading
Content angles
- Create a tutorial series on implementing specific trading models discussed in the book.
- Analyze and compare different types of financial data sources used in the repository.
- Develop a case study showcasing how to design, backtest, and evaluate a trading strategy using ML techniques.
Who should care
Data scientists, quantitative analysts, and developers interested in applying machine learning to financial markets.