🎬 Movie Recommendation System

A smart Movie Recommendation System built using Machine Learning and Python, designed to help users discover movies they'll love based on their preferences or previously watched content.

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🔍 Features

• 📌 Content-Based Filtering – Recommends movies based on genres, cast, director, and plot similarity.
• 📊 Cosine Similarity / TF-IDF – Utilizes NLP techniques for comparing movie descriptions.
• 🎯 Search Functionality – Find similar movies by entering the name of any movie.
• ⚡ Fast & Lightweight – Optimized for performance and quick results.
• 🧠 Optionally Integrates ML models like KNN or Collaborative Filtering.

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Setup

1. Install dependencies (globally, no venv required):

   pip install django pandas

2. Run migrations:

   python manage.py migrate

3. Start the server:

   python manage.py runserver

File Structure

• movie_list.pkl — Pandas DataFrame with movie titles
• similarity.pkl — Precomputed similarity matrix
• recommend/posters.json — Mapping of movie titles to poster URLs
• recommend/views.py — Django views for home and recommendations
• recommend/templates/recommend/home.html — Main UI template

Customization

• To change the number of home page posters, edit the value in views.py (count >= 12)
• To update the look, edit the CSS in home.html
• To add more movies or posters, update the pickle and JSON files

Credits

• Poster images from TMDB
• UI inspired by Netflix

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Enjoy your personalized movie recommendations!