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This is a machine learning project that aims to recommend songs to users based on their listening history and rating. Non-negative Matrix Factorization (NMF) is used for song recommendation.

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Varun-N-M/Songs-recommendation_using_NMF

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Songs-recommendation_using_NMF

Project name:

Songs recommendation

Tools used:

  • Python

Packages:

  • Numpy

  • Pandas

  • Matplotlib

  • Scikit learn

Two methods are used in Model:

  • Using Eucliden distance between users and recommending top songs heard by nearest users

  • Using Kmeans cluster to create clusters based on genres and recommending top songs

About

This is a machine learning project that aims to recommend songs to users based on their listening history and rating. Non-negative Matrix Factorization (NMF) is used for song recommendation.

Topics

machine-learning-algorithms nearest-neighbors non-negative-matrix-factorization nmf-decomposition

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