fklearn: Functional Machine Learning

This code accompanies the the paper Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture (https://arxiv.org/pdf/2112.08534.pdf).

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

Vlad helps you distribute your stake on Numer.ai

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

A vectorized implementation of py_vollib, that supports numpy arrays and pandas Series and DataFrames.

A framework for quantitative finance In python.

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

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.

Portfolio and risk analytics in Python

A unified framework for machine learning with time series

A Python package for time series classification

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

AutoML tools for solving Time-Varying High-Dimensional Ordinal Regression Problems

Solid Numerai pipelines

Code and Notes for fat-tailed statistics.

GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.

Downloads data from Yahoo Finance, generates features, trains a model and submits the predictions to the tournament.

Repository containing notebooks of my posts on Medium

ARCH models in Python

A curated list of awesome numerai libraries, tutorials and other resources.

QuantStart.com - QSTrader backtesting simulation engine.

Notebooks based on financial machine learning.

Example Machine Learning Scripts for Numerai's Tournament

M5 Uncertainty kaggle competition, 3rd place solution

Python / R / Mathematica / ___ code and commentaries based on Nassim Taleb's "Statistical Consequences of Fat Tails" - Feel free to contribute

Python version of the Matlab RobustSP toolbox (https://github.com/RobustSP)