Lists (1)
Stars
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
2 books and related source codes for algorithmic trading.
Chemical reaction data & benchmarks. Extraction and cleaning of data from Open Reaction Database (ORD)
Notes, exercises and other materials related to causal inference, causal discovery and causal ML.
Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code.
Top training materials in quantitative finance
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Code for: "A Generalised Signature Method for Time Series"
Reimplementation of Geoffrey Hinton's Forward-Forward Algorithm
A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
An Interview Primer for Quantitative Finance
Source code for Algorithmic Trading with Python (2020) by Chris Conlan
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Repository for the Lux AI Challenge, season 2 (NeurIPS 23). Hosted on @kaggle
Machine Learning for Algorithmic Trading, Second Edition - published by Packt
Open source platform for the machine learning lifecycle
A playbook for systematically maximizing the performance of deep learning models.
Code for the paper: Putting An End to End-to-End: Gradient-Isolated Learning of Representations
Code for the paper: Complex-Valued Autoencoders for Object Discovery
This repository contains implementations and illustrative code to accompany DeepMind publications
An example of time series augmentation methods with Keras
Hydra is a framework for elegantly configuring complex applications
Implementation of modern data augmentation techniques in TensorFlow 2.x to be used in your training pipeline.
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas…