THINK989/Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN 开源项目中文解读：技术栈、适用场景与上手建议

项目介绍

THINK989/Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN 是一个托管在 GitHub 上的开源项目，主要使用 Python 编写，采用 MIT License 许可证，目前获得 207 个 Star、41 次 Fork。

仓库全名: THINK989/Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN

README 摘要

Real Time Stock Market Forecasting This repository contains an implementation of ensemble deep learning models to forecast or predict stock price. We used Alpha Vantage API to pull stock data(open,high,low,close,volume) and scraped news headlines from inshorts to perform sentiment analysis. The code and the images of this repository are free to use as regulated by the licence and subject to proper attribution…

完整内容见 GitHub 原始 README 或本页。

常见问题

Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN 用什么语言开发？

主要使用 Python 编写，采用 MIT License 许可证，目前有 207 个 Star。

Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN 可以免费商用吗？

如何获取 Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN 的源码？

可以直接克隆仓库：git clone https://github.com/THINK989/Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN.git，默认分支为 master；安装与运行步骤见仓库 README。

Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN 最近还在维护吗？

仓库最近一次更新为 2月13日，当前有 2 个未关闭 Issue；Star 数为 207，可作为社区活跃度的参考。

关于

ensemble gru keras lstm rainbow-dqn real-time-prediction stock-price-forecasting tensorflow trade-bot

MIT License
207 Stars
41 Forks
7 Watching

简要分析

热度分

296

价值分

137

活跃状态

活跃

GitHub

语言占比

Jupyter Notebook

Python

贡献者

THINK989

Real Time Stock Market Forecasting

This repository contains an implementation of ensemble deep learning models to forecast or predict stock price. We used Alpha Vantage API to pull stock data(open,high,low,close,volume) and scraped news headlines from inshorts to perform sentiment analysis.

The code and the images of this repository are free to use as regulated by the licence and subject to proper attribution:

Shah, Raj and Tambe, Ashutosh and Bhatt, Tej and Rote, Uday, Real-Time Stock Market Forecasting using Ensemble Deep Learning and Rainbow DQN. 
Available at SSRN: https://ssrn.com/abstract=3586788 or http://dx.doi.org/10.2139/ssrn.3586788.

Architecture

Getting Started

It would be a better idea to create a conda environment and work in isolation

Create a virtual environment

conda create -n envname python=3.6.8 anaconda 
conda activate envname

Use conda deactivate to deactivate the environment

Clone this repository

git clone --depth 1 https://github.com/THINK989/Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN.git && cd Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN

Install the requirements

pip install -r requirements.txt

Get an Alpha Vantage API key

To run animate.py you require a free Alpha Vantage API Key. Enter the key in key='' parameter inside the animate.py file

ts = TimeSeries(key='',output_format='pandas')

Run python script

To vizualize the forecast. Remember the data pulled by the API will not update the plot if the market is closed.

python animate.py

To get heatmap visualization for correlation analysis on ^NSEI(Nifty50)

python heatmap.py

License

This repository is distributed under MIT License

and

respective LICENSE under directories

forecast/LICENSE
or 
rainbow/LICENSE

for thier independent code usage.

Acknowledgements

@huseinzol05 for deep learning models
@sentdex for plotting tutorials
Vader Sentiment
Alpha Vantage API for stock data
Inshorts for news headlines

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Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN