ML for Trading - 2nd Edition This book aims to show how ML can add value to algorithmic trading strategies in a practical yet comprehensive way. It covers a broad range of ML techniques from linear regression to deep reinforcement learning and demonstrates how to build, backtest, and evaluate a trading strategy driven by model predictions.

Updated 2023-09-15 11:16:05 +08:00

It is a Technical Analysis library useful to do feature engineering from financial time series datasets (Open, Close, High, Low, Volume). It is built on Pandas and Numpy. Project url: https://technical-analysis-library-in-python.readthedocs.io/en/latest/

Updated 2023-09-15 11:16:05 +08:00

MachineLearningStocks is designed to be an intuitive and highly extensible template project applying machine learning to making stock predictions. Source from: https://github.com/robertmartin8/MachineLearningStocks Caution!!! As of Feb 2021: MachineLearningStocks is no longer actively maintained

Updated 2023-09-15 11:16:05 +08:00