🎵 Music Recommendation System

A Music Recommendation System that intelligently suggests songs to users based on their listening history, preferences, and music patterns.
The project leverages machine learning and recommendation algorithms such as content-based filtering, collaborative filtering, and hybrid models to deliver a personalized listening experience.

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🚀 Features

• 🎧 Personalized song recommendations
• 📊 Supports content-based filtering (based on song features like genre, mood, tempo)
• 👥 Collaborative filtering using user similarity and interaction history
• 🔄 Hybrid approach for improved accuracy
• 📂 Dataset-driven analysis for better predictions
• ⚡ Scalable and adaptable for real-world streaming platforms

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🛠️ Tech Stack

• Programming Language: Python
• Libraries & Tools:
  • pandas, numpy → Data handling
  • scikit-learn → Machine Learning models
  • surprise → Recommendation algorithms
  • matplotlib, seaborn → Data visualization

credit by : likhita , neha and vidhi