This repository contains the code for our project Movie Recommendation System, developed during our Data Scientist training at DataScientest.
The goal of this project is to create a recommendation system based on the MovieLens 25M dataset using collaborative filtering and model optimization through Deep Learning algorithms.
This project was developed by the following team :
To run the code you need to download the data from MovieLens and extract/save it to the directory data/raw:
├── LICENSE
├── README.md <- The top-level README for developers using this project.
├── data <- Should be in your computer but not on Github (only in .gitignore)
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── models <- Trained and serialized models, model predictions, or model summaries.
│
├── notebooks <- Jupyter notebooks.
You will need to install the dependencies (in a dedicated environment) :
pip install -r requirements.txt
Project based on the cookiecutter data science project template. #cookiecutterdatascience