I'm a data scientist who is passionate about learning and making data science more approachable through creative projects. My go-to language for project work is Python, and I find joy in exploring music as a unique data source, using it to dive into new machine learning techniques and mathematical concepts.
In my latest project, I built a CRNN neural network to automatically detect choruses in songs from my favorite Spotify playlists. You can check out the code and detailed writeup in the chorus-detection repository. Additionally, I maintain a collection of case studies where I apply various machine learning techniques, such as random forests and XGBoost for customer churn prediction or clustering algorithms for customer segmentation, to real-world problems across different industries.
If you find value in any of my projects or insights, feel free to star the relevant repositories or follow me on GitHub. I'm always excited to connect with fellow data enthusiasts and learn from each other!
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- And more at dennisvdang.com
