Popular GitHub Repositories for Bitcoin Cash Chip

阿布量化交易系统(股票，期权，期货，比特币，机器学习) 基于python的开源量化交易，量化投资架构

A list of ICs and IPs for AI, Machine Learning and Deep Learning.

Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering

基金,大盘,股票,虚拟货币状态栏显示小应用,基于Electron开发,支持MacOS,Windows,Linux客户端,数据源来自天天基金,蚂蚁基金,爱基金,腾讯证券等

Predict Cryptocurrency Price with Deep Learning

Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent

Deep Reinforcement Learning based Trading Agent for Bitcoin

Free self-hosted market-making bot for crypto projects & token issuers. Volume, spread, liquidity, price ranges, and dynamic order books — all in one.

Code for testing various M1 Chip benchmarks with TensorFlow.

Exploiting Bitcoin prices patterns with Deep Learning.

Applying Machine Learning and AI Algorithms applied to Trading for better performance and low Std.

Machine learning models for time series analysis

Predict bitcoin price with deep learning

Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot

Enterprise self-hosted Bitcoin Core automated trading software and trading bot, with DCA bot configuration, on-premise TWAP/VWAP strategy scripts, dynamic fee management, CCXT exchange adapter, compliance reporting, OTC desk integration, HSM hardware signing, real-time PnL metrics, and advanced strategy view windows.

Repository collecting papers about neuromorphic hardware, such as ASIC and FPGA implementations of SNNs and stuff.

A Bitcoin trade robot based on Tensorflow LSTM model.Just for fun.

A detailed summary of "Designing Machine Learning Systems" by Chip Huyen. This book gives you and end-to-end view of all the steps required to build AND OPERATE ML products in production. It is a must-read for ML practitioners and Software Engineers Transitioning into ML.

Trading environnement for RL agents, backtesting and training.

Time Series Forecast with Bitcoin value, to detect upward/down trends with Machine Learning Algorithms