Description

In this project, I aimed to uncover what factors influence the popularity of a song on Spotify. Using data from Spotify’s API and a custom database hosted on BigQuery, I analyzed song attributes like valence, loudness, energy, and lyrics. I trained machine learning models to predict track popularity based on these attributes and found that factors like loudness and explicitness significantly correlate with popularity. This project showcases the use of data analysis and machine learning to provide insights into the music industry and how certain attributes drive song success.

Project Report

Github Repo