This project is an attempted solution to the Kaggle problem "Indoor Logation & Navigation". It uses a Long Short-Term Memory (LSTM) model to analyze a pre-processed version of the data which only contains Wi-Fi features of a certain strength and returns the results.
This project was completed for course credit for CSI 5325 at Baylor University, taught by Dr. Pablo Rivas.
I constructed this model using the Keras API for Python. This repository contains the code which produces the model and my report, written in LaTeX.
In order to run the project, you will need to download the data files from the link given above and place them in a data/ directory with two subdirectories, test/ and train/. Next, you will need to initialize your local environment by installing the Python dependencies using pip:
pip install -r requirements.txt
I recommend first installing and using a virtual environment as follows:
python -m venv venv
source venv/bin/activate
Finally, you can run the project as follows:
python main.py