🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

A curated list of practical financial machine learning tools and applications.

Implementation of "Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading." In Findings of ACL2021

TensorFlow code and pre-trained models for BERT

Atreyu's integration of IB Native API with backtrader

Experimental code supporting the results presented in the scientific research paper entitled "An Application of Deep Reinforcement Learning to Algorithmic Trading"

Source code for Deep Fundamental Factor Models, https://arxiv.org/abs/1903.07677

Implemented some mathematical processings used in the Barra risk model

The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.

Interpretability and explainability of data and machine learning models

https://arxiv.org/abs/1805.01104

SDK for Financial Modeling Prep's (FMP) API

A brief description on how to use Financial Modeling Prep Api

A curated list of awesome libraries, packages, strategies, books, blogs, tutorials for systematic trading.

Learn quantitative finance with this comprehensive lecture series. Adapted from the Quantopian Lecture Series. Uses free sample data.

Book about interpretable machine learning

Material for the exercise sessions of master course Machine Learning for Economic Analysis @UZH

Machine Learning for Algorithmic Trading, Second Edition - published by Packt

Code for Machine Learning for Algorithmic Trading, 2nd edition.

Repo for code examples in Quantitative Finance with Python by Chris Kelliher

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

Website dedicated to a book on machine learning for factor investing

Learn Algorithmic Trading, Published by Packt