Content-Based Movie Recommendation System

This project implements a Content-Based Recommendation System using metadata from movies such as genres, cast, crew, and plot overviews to suggest similar movies. The system is designed to provide personalized movie recommendations based on the content a user already likes or is viewing.

📌 Project Overview

🔍 Objective

To recommend movies that are similar in content to a selected movie using:

• Text feature extraction (TF-IDF)
• Cosine similarity
• Content attributes: overview, genre, top cast, and director

📁 Dataset

Datasets from the The Movies Dataset are used:

• movies_metadata.csv
• credits.csv

Make sure both are placed in the same directory as the script.

🛠️ Features Used

• overview – Plot summary of the movie
• genres – Movie genres (Action, Comedy, etc.)
• cast – Top 3 cast members
• crew – Director of the movie

All of these are combined into a single string (called soup) for vectorization.

📦 Dependencies

Install the required Python packages using pip:

pip install pandas scikit-learn