Movie Recommendation System - Python Part

This part of the project handles data preprocessing, model training, recommendation generation, and evaluation.

Table of Contents

• Overview
• Structure
• Setup
• Usage
• License

Overview

The Python part of the project reads movie and ratings data, preprocesses it, splits it into training and test sets, trains a collaborative filtering model, generates recommendations, and evaluates the model's performance.

Structure

python/
├── Dockerfile
├── requirements.txt
├── preprocess.py
├── main.py
├── database.py
├── similarity.py
├── recommendations.py
└── tests/
    ├── test_database.py
    ├── test_integration.py
    ├── test_preprocess.py
    ├── test_recommendations.py
    └── test_similarity.py

Setup

Prerequisites

• Python 3.x
• Install dependencies using requirements.txt:

pip install -r requirements.txt

Usage

Data Preprocessing

Run the preprocessing script to preprocess the data and split it into training and test sets:

python preprocess.py

Model Training and Recommendation Generation

Run the main script to train the model, generate recommendations, and evaluate the model:

python main.py

Running Tests

pytest -s tests

License

This project is licensed under the MIT License.