Stock predictions with LSTM

Description

This application exemplifies the implementation of an LSTM network for the prediction of stock values ​​in the market.

Stack

• Python:
  • Keras
  • Matplotlib
  • Numpy
  • Pandas
  • Scikt Learn
  • Jupiter Notebook

Setup

First of all you must clone the repository:

git clone https://github.com/jezbravo/lstm.git
cd lstm

Create a virtual environment to install dependencies in and activate it:

python.exe -m venv venv
.\venv\Scripts\activate

Then install the dependencies:

(venv)pip install -r requirements.txt

Note the (venv) in front of the prompt. This indicates that this terminal session operates in a virtual environment set up by "venv".

Once everything is ready:

(venv)python.exe .\app.py

Demo

Both the dataset and the training parameters can be adjusted to improve the performance of the model and obtain better results.

You can review the development of the project at the following link: LSTM Notebook.