verigibest Goto Github PK

ai-blog

Accompanying repository for Let's make a DQN / A3C series.

alphalens

Performance analysis of predictive (alpha) stock factors

awesome-quant

**的Quant相关资源索引

batchrenormalization

Batch Renormalization algorithm implementation in Keras

char-rnn

Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch

deep-q-learning

Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

deeplearningflappybird

Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).

deeptrade_keras

easyquant

股票量化框架，支持行情获取以及交易

fastweixin

极其方便的实现微信公众平台服务端开发，2行代码完成服务器绑定，3行代码实现用户消息监听

lstm

Minimal, clean example of lstm neural network training in python, for learning purposes.

lstm-neural-network-for-time-series-prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

rqalpha

A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities

sharpefolio

Stock portfolio optimizer in Python based on least correlated moving sharpe / sortino ratios.

simple-http-server

Simple http server in Rust (Windows/Mac/Linux)

stock-prediction

Stock price prediction with recurrent neural network. The data is from the Chinese stock.

stock-price-prediction

A practice project for machine learning and stop price prediction

stock-rnn

Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.

stock_market_prediction

Team Buffalox8 predicts directional movement of stock prices.

stock_market_reinforcement_learning

This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

tensorflow-for-stock-prediction

Use Tensorflow to run CNN for predict stock movement. Hope to find out which pattern will follow the price rising.

vnpy

基于Python的开源量化交易平台开发框架

wechatpy

WeChat SDK for Python

weixin-java-tools

可能是目前最好最全的微信Java开发工具包，支持包括微信支付、开放平台、小程序、企业号和公众号等的开发

zipline

Zipline, a Pythonic Algorithmic Trading Library