Movie Recommendation with Flask and scikit-learn
W A simple yet effective Movie Recommendation System built with Python, Flask, and scikit-learn. It suggests similar movies based on the description (overview) of a selected movie using Content-Based Filtering and TF-IDF Vectorization.
Project Summery
A simple yet effective Movie Recommendation System built with Python, Flask, and scikit-learn. It suggests similar movies based on the description (overview) of a selected movie using Content-Based Filtering and TF-IDF Vectorization.
🚀 Features
- 🔍 Search for a movie title
- 🧠 Recommends top 5 similar movies based on content
- 📦 Lightweight and easy to run locally
- 🌐 Simple web interface using Flask
🛠 Technologies Used
- Python 3.x
- Flask
- Pandas
- Scikit-learn
- HTML/CSS
📥 Dataset
This project uses a simplified version of the TMDB 5000 Movie Dataset. Your movies.csv should have at least the following columns:
id,title,overview
1,Toy Story,A story of a boy and his toys that come to life.
2,Jumanji,A board game that comes to life.
...
🔧 Installation
1. Clone the Repository
git clone https://github.com/sujit-codezen/movie_recommendation_system.git cd movie-recommender
2. Create Virtual Environment (optional but recommended)
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
3. Install Dependencies
pip install -r requirements.txt
4. Run the App
python app.py
DEMO
