NOTE: There is some issue in loading notebook on github, therefore to check the full notebook and better visualizations please check Kaggle Notebook
This repository contains Music Recommendation System using Spotify Dataset.
To do this, I presented some of the visualization processes to understand data and done some EDA(Exploratory Data Analysis) which helps to select features that are relevant to create the best Music Recommendation Engine.
Here, the target value is 'popularity'. Before doing analysis, I have checked for the Feature Correlation by considering a few features and for that, I'm going to use the yellowbrick package. You can learn more about it from the documentation.
