The model used is an LSTM neural network. The aim was to create a model
that's able to predict the closing price of a given stock one day into the future.
In order to do this, the model takes as input the last 20 closing prices of the given stock.
The data used to train the model consists of the stocks that are part of the S&P500 stock index fund,
meaning that the model is primarily adjusted for 'blue chip' stocks that don't tend to have
large price fluctuations.
In order to install all the required dependencies run:
~/$ git clone https://github.com/BouzoulasDimitrios/Stock-price-prediction-app.git
~/$ cd Stock-price-prediction-app/
~/Stock_price_prediction_app$ pip install -r requirements.txt
In order to run the desktop application:
~/Stock_price_prediction_app$ cd Desktop_application/
~/Stock_price_prediction_app/Desktop_application$ python3 main.py
