liamkl's Stars
freqtrade/freqtrade
Free, open source crypto trading bot
stefan-jansen/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
AI4Finance-Foundation/FinRL
FinRL: Financial Reinforcement Learning. 🔥
jlevy/og-equity-compensation
Stock options, RSUs, taxes — read the latest edition: www.holloway.com/ec
nautechsystems/nautilus_trader
A high-performance algorithmic trading platform and event-driven backtester
kzl/decision-transformer
Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.
AminHP/gym-anytrading
The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)
ZhengyaoJiang/PGPortfolio
PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).
AI4Finance-Foundation/FinRL-Tutorials
Tutorials. Please star.
Ahmkel/Keras-Project-Template
A project template to simplify building and training deep learning models using Keras.
nordquant/complete-dbt-bootcamp-zero-to-hero
Supplementary Materials for the The Complete dbt (Data Build Tool) Bootcamp Udemy course
shorepine/tulipcc
The Tulip Creative Computer - a portable Python synthesizer for music and graphics
newdigate/eurorack-awesome
awesome eurorack diy and opensource
AI4Finance-Foundation/FinRL_Podracer
Cloud-native Financial Reinforcement Learning
cove9988/TradingGym
Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.
ncbi/dbsnp
dbSNP
CMACH508/DeepTrader
EthanBraun/DeepPortfolioManagement
An implementation of the paper "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"
DjangoPeng/PredictionModel
jarney/fftmusings
Project applying neural networks to audio data, in particular, attempting to train an LSTM to recognize and reproduce music based on raw music samples. Uses FFT/Phase Vocoder for input followed by an autoencoder and then an LSTM with a mixture density cost function to model the sequence of data.