🎬 Movie Recommendation Engine

A content-based recommendation system that suggests similar movies using cosine similarity and NLP techniques. The system analyzes movie features like genres, director, cast, and keywords to provide personalized suggestions.

🔍 How It Works

• Data Processing: Combines multiple features (genres, director, cast, keywords) into a single text vector
• Vectorization: Uses CountVectorizer to convert text into a numerical matrix
• Similarity Scoring: Computes cosine similarity between movies to find the closest matches
• Recommendation: Returns the most similar movies to any given input title

⚙️ Technical Implementation

• Built with Python's scikit-learn ecosystem (pandas, numpy, sklearn)
• Implements cosine similarity for measuring movie similarity
• Processes the Movie Dataset containing comprehensive movie metadata

🚀 How to Use

1. Clone the repository
2. Install dependencies: pandas, numpy, scikit-learn
3. Run the script and input your favorite movie
4. Get 10 most similar movie recommendations

python movie_recommender.py

📊 Key Features

• Handles missing data gracefully
• Customizable feature combination
• Efficient similarity scoring
• Easy-to-understand recommendation output