PROJECT
2019Apple Music Streaming Analysis
Flatiron
Module project for the Data Science Immersive program. Analyzed dataset of my personal streaming activity. Leveraged natural language processing techniques to classify the content and sentiment of the song lyrics. Identified key themes, trends, and patterns in how the lyrics differed between genres.
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Overview
Description:
This data science project investigated what elements in song lyrics determine their genre classification. Using NLP techniques, I developed and tested various models to predict musical genres based solely on lyrical content from a personal music listening history dataset spanning three years.
Project Goals:
Analyze what textual features in lyrics correlate with specific music genres
Build and compare NLP classification models to predict song genres from lyrics
Address challenges of class imbalance in the dataset
Achieve high accuracy prediction across multiple genres despite data limitations
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