RBM Movie Recommender

This project implements a collaborative recommendation engine using a Gaussian-Bernoulli Restricted Boltzmann Machine (RBM).

Methodology

The model is a Restricted Boltzmann Machine (RBM) optimized for collaborative filtering. A Gaussian-Bernoulli variant was chosen to handle continuous movie ratings (0.5 to 5.0) instead of simple binary inputs.

Dataset

The system uses the MovieLens small dataset.

Requirements

• Python 3.x
• PyTorch
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Scikit-learn
• Ipywidgets

Usage

1. Open rbmRecommender.ipynb in a Jupyter environment.
2. Run the notebook cells to:
   • Download and preprocess the dataset.
   • Train the RBM model.
   • Generate and evaluate recommendations.
   • Use the interactive search box to get top 10 recommendations for a specific User ID.