Stock Price Predictor

Predict price for various stocks and cryptocurrencies using historical daily data

This Python Notebook aims to predict closing price for stocks using XtremeGradient Boost Machine Learning Algorithm as accurately as possible and uses AlphaVantage REST API for fetching historical data points

Installation

Windows and Mac OS X and Linux :

pip install numpy
pip install matplotlib
pip install seaborn
pip install jupyter-notebook
pip install scikit-learn
pip install xgboost

Usage example

To run this all you need is a AlphaVantage API Key which can be found Here

Development setup

To Setup the Notebook Install the Above Dependencies and Replace [redacted] with your Alphavantage API Key.

Release History

• 0.0.3 (WIP)

  • Add Support to search for symbols before requesting data to avoid empty CSV

• 0.0.2

  • Added Support for Cryptocurrency

• 0.0.1

  • Basic Skeleton is Ready and running

Meta

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Contributing

1. Fork it
2. Create your feature branch (git checkout -b feature/fooBar)
3. Commit your changes (git commit -am 'Add some New Feature')
4. Push to the branch (git push origin feature/fooBar)
5. Create a new Pull Request