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machine-learning

This project is for predicting variation of stock price in the future. using keras with tensorflow in the backend.

Project Purpose

stock prediction is one of the most concerning question. This project wants to find a good machine learning method on predicting future stock price variation. This may help to evaluate whether a stock is worth investing.

Getting Started

Prerequisites

jupyer notebook installed on local or remote machine.

How to use

clone or download the project. Running on Jupyter Notebook. For more details read the markdown of data_processing.ipynb.

File Structure

  • data_processing.ipynb is the entry of this project.
  • data_fetching.ipynb is the data fetching code.
  • ./NASDAQ is the stock folder, every '*.csv' represents a single stock.

Built With

  • Anaconda - python runtime environment with scientific packages
  • Jupyter Notebook - open-source web application running python

Data Source

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License

This project is licensed under the MIT License - see the LICENSE.md file for details

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