From Rail to Real Estate: Award winning Tableau Dashboard

Developed a machine learning pipeline that fuses Natural Language Processing (NLP) with audio feature analysis to quantify the impact of lyrical themes on commercial music success.

Task

End-to-end data science lifecycle: from scraping and cleaning complex text data to building and evaluating predictive models (Random Forest, Gradient Boosting) to forecast song popularity

Role

Data Scientist
Tech

Python, Scikit-learn, LDA (Latent Dirichlet Allocation), Spotify API, Genius API, Pandas, NLTK
Status

Completed

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Topic Modelling of Song Lyrics to Predict Billboard Longevity