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© 2025 Sarah Elsharkawi
fueled by coffee
And the Grammy
Goes To…
A Predictive Analysis of
Grammy Award Outcomes
This is my senior thesis: a data-driven analysis of Grammy outcomes, using predictive modeling to uncover trends in music industry recognition.
What makes a song Grammy-worthy - commercial
success, artistic merit, or some elusive
balance of both?
This project investigates that question through a data-driven lens, using machine learning to predict Grammy Award winners from 2004 to 2025.
I built a full pipeline from data collection and cleaning to model training and evaluation, drawing on audio features, Billboard chart performance, and Genius lyrics across three categories: Song of the Year, Record of the Year, and Best Rap Song.
My Approach
Top 3 Predictions per Category
Swipe through the years to see how the model ranked each category - actual winners highlighted in green!
Across three Grammy categories and four years, the model placed the true winner in its top 3 predictions in 11 out of 12 cases!
Want to dive deeper into the process, results, and technical detail? See the full presentation here!
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