aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

A game theoretic approach to explain the output of any machine learning model.

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

A collection of various deep learning architectures, models, and tips

Automatic extraction of relevant features from time series:

Python toolkit for quantitative finance

Recipes for using Python's pandas library

Google Brain AutoML

Code for Tensorflow Machine Learning Cookbook

Portfolio and risk analytics in Python

Collection of notebooks about quantitative finance, with interactive python code.

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

Technical Analysis Library using Pandas and Numpy

This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.

A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/

Beaker Extensions for Jupyter Notebook

List of papers, code and experiments using deep learning for time series forecasting

A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.

📊⚽ A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.

Machine Learning in Finance: From Theory to Practice Book

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

Machine Learning in Asset Management (by @firmai)

A site that displays up to date COVID-19 stats, powered by fastpages.

Getting started with soccer analytics

fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!

Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at

Some Python Implementations of the Kalman Filter

Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ram Seshadri. Collaborators welcome.