bhumikabiyani / music_recommendation

Music Recommender System

This project implements a Music Recommender System using Streamlit and Spotipy. It allows users to discover new music based on their favorite tracks.

Features

• Song Recommendation: Recommends similar songs based on user input.
• Visual Representation: Displays album covers and Spotify links for recommended songs.
• Customization: Users can specify the number of recommendations they want to receive.

Technologies Used

• Python
• Streamlit
• Spotipy (Python library for Spotify Web API)
• Pandas
• Scikit-learn (for TF-IDF vectorization and cosine similarity)
• NLTK (for natural language processing tasks)

Setup Instructions

1. Clone the repository:

   git clone https://github.com/your-username/music-recommender-system.git
   cd music-recommender-system

2. Install dependencies:

   pip install -r requirements.txt

3. Run the Streamlit app:

   streamlit run app.py

4. Use the Music Recommender:

   • Select or type in a song name.
   • Specify the number of recommendations.
   • Click on "Show Recommendation" to see the results.

Screenshots

Acknowledgments

• Thanks to Spotipy for the Python library to interact with the Spotify Web API.
• Inspired by the idea of recommending music based on user preferences.