The files environment.yml, requirements.txt make it easy to replicate the environment required for running the model.

1. For anaconda:
   
   1. To install anaconda, refer this
      
   2. The base directory contains 'environment.yml' file. To replicate the same environment:

      conda env create -f environment.yml

2. For python3 virtual environment:
   
   1. To install virtualenv, refer this

      pip install virtualenv
      virtualenv --python=python3 ml-stock-prediction

   2. The base directory contains 'requirements.txt' file. To install the required packages:

      pip install -r requirements.txt

Though the datasets folder has some symbol stock prices. You can populate with more.

python get_data.py [symbols]

You can run the model on a list of symbols supplied as command line arguments.

python main.py [symbols]