Song Genre Classification with Spotify API

Led the data gathering and preprocessing phase for a machine learning project aimed at predicting song genres using Spotify's Web API. As part of a three-person team, I designed and implemented a sophisticated data collection strategy that enabled robust genre classification across six major categories (Rock, Pop, Rap/Hip-Hop, Classical, Jazz, and Other).

Key Contributions:

Engineered an extensive genre classification system using nested dictionaries to map subgenres to main genres, significantly expanding our dataset beyond Spotify's 900-record API limit .

Developed automated data collection pipelines to extract audio features, artist information, and album metadata from Spotify's API .

Implemented validation functions to ensure data quality and prevent unnecessary API calls.

Delivered a concise presentation of the project’s data gathering methodology, effectively communicating key insights and technical achievements to stakeholders in under three minutes.