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.
Project name:
Songs recommendation
Tools used:
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
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.