Stock Prediction

NOTE: STOCK PREDICTION IS VOLATILE. DO NOT USE THIS AS YOUR PREDICTION MODEL.

File info:

1. stock-info.ipynb
2. stock-lstm.ipynb

stock-info.ipynb: Contains data visualizations for the index predicted. Please be careful in inputting the correct index. Data source must be either Kaggle or Alphavantage. Handling other data sources will be implemented during revision.

stock-lstm.ipynb: Contains the actual code including model implementation, error of the model and quantitatively comparing Simple and Stacked LSTM networks.

Clone the repository:

$ git clone https://github.com/akshathmangudi/Stock-Prediction.git
$ Stock-Prediction/

Table of Contents

• Creating a virtualvenv
• Dependencies
• Run the notebook

Creating virtualvenv

For Python 3.6+ users:

$ python -m venv /path/to/virtualenv

For activation of virtualenv: bash/zsh:

$ source <venv>/bin/activate

fish:

$ source <venv/bin/activate.fish

cmd.exe:

C:\> <venv>\Scripts\activate.bat

PowerShell: 
PS C:\> <venv>\Scripts\activate.ps1

For conda users, the following commands are to be sequentially passed into your terminal:

$ conda -V
$ conda update conda
$ conda create -n <envname> python=x.x anaconda
$ conda activate <envname>

For deactivation:

$ conda deactivate

Dependencies

The dependencies required to run this notebook can be installed using the below command.

$ pip install -r requirements.txt

Run the notebook

For stock-info:

jupyter notebook stock-info.ipynb

For stock-lstm:

jupyter notebook stock-lstm.ipynb

Project by Akshath Mangudi (2023)