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Data Science Workshops

These are data science tutorials that I prepared

for conference and independent workshops.

I was the sole instructor for all the workshops.

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Click on workshop title to access tutorial.

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Note: These are R tutorials.

Clustering

Music Genres

The aim of this procedure was to identify clusters among different music genres using Spotify data. The input variables for this analysis were number of songs and popularity scores per artist. This is the tutorial for one of the two workshops that I directed at the Arizona Research Bazaar 2021 (ResBaz 2021).

Machine Learning

Spotify Audio Features and Music Genres

The aim of this procedure was to compute a classifier model using Spotify audio features as predictors of music genres. The algorithms selected for this purpose were Random Forest,

K-Nearest Neighbor, and Boosted Trees. Thus, the evaluation metrics to assess the model were Precision, Recall, Area Under Curve (Roc-Auc), and Specificity. This was a preliminary analysis for one of the studies in my dissertation project.

Sentiment Analysis

Song lyrics of Evanescence

The aim of this procedure was to conduct a Sentiment Analysis on the song lyrics of Evanescence. I analyzed underlying themes and emotions depicted in lyrical text from the band and gained insights by computing text analysis procedures as well as data visualizations. This is the tutorial for one of the two workshops that I directed at the Arizona Research Bazaar 2021 (ResBaz 2021).

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