🎬 Movie Recommendation System

A content-based movie recommendation system that suggests films based on genre similarity and user preferences using cosine similarity and PCA visualization.

🚀 Features

• Content-Based Filtering: Uses movie genres to calculate similarity
• User Profile Analysis: Builds personalized genre preferences for each user
• Cosine Similarity: Measures similarity between movies based on genre vectors
• PCA Visualization: 2D visualization of recommendation diversity
• Customizable Recommendations: Adjustable number of recommendations

📊 How It Works

1. Data Loading: Reads movie metadata and user ratings
2. Genre Encoding: One-hot encodes movie genres into feature vectors
3. Similarity Calculation: Computes cosine similarity between all movies
4. User Profiling: Analyzes user's rating history to determine genre preferences
5. Recommendation Generation: Suggests movies similar to user's highly-rated films
6. Visualization: Projects recommendations into 2D space using PCA

🛠️ Installation

1. Clone the repository:

git clone https://github.com/yourusername/movie-recommendation-system.git
cd movie-recommendation-system