Starred repositories
LightGBM Baseline Model for Quantitative Trading using Stock Market Data
Apply machine learning algorithms in the financial market. Ensemble Model, including XGBoost, LightGBM, CNN, ResNet and LSTM.
pure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks
A new way to see and navigate directory trees : https://dystroy.org/broot
Curated list of Go design patterns, recipes and idioms
Creating notes with the zettelkasten note taking method and storing all notes on github
FinRL_Crypto: Cryptocurrency trading of FinRL
An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models
Fast minimalist backtesting, sympathetic to the quant process.
Details on how to get Binance public data
🌙 LunarVim is an IDE layer for Neovim. Completely free and community driven.
A skeleton for creating a neuro-evolution reinforcement learning trading bot with a Keras neural network.
Automated Trader (at). This is a framework for building trading bots.
Investment Research for Everyone, Everywhere.
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Elegant Scraper and Crawler Framework for Golang
A curated list of insanely awesome libraries for golang, packages and resources for Quants (Quantitative Finance)
Performant financial charts built with HTML5 canvas
📈Lightweight k-line chart that can be highly customized. Zero dependencies. Support mobile.（可高度自定义的轻量级k线图，无第三方依赖，支持移动端）
// Aesthetic, dynamic and minimal dots for Arch hyprland
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.