I'm currently working on a side project that I've had in my head for a while. There are a few blogs and articles out there about measuring and ranking the rhyme styles of different rappers. And while there is nothing wrong with ranking your favorite rappers (I do this from time to time and it's pretty hard), I make no assumption that I can justify those rankings based on a single dimension of the multi-dimensional lyric-space. My intention here isn't to assign hard quantities to different rappers, but to better visualize their styles based on their rhyme patterns. While other rhyme detection algorithms do a great job of identifying complex rhyming structure and multi-syllabic rhymes to quantify rhyme, my understanding was that the rhyme definitions were somewhat strict. For example, a multi-syllablic rhymes could only be counted as far as the syllable sequences matched almost exactly . If you're a student of lyrics, you might agree that the best rhymes ar
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I had the opportunity to work as a Fellow with Insight Data Science for the last couple months, an experience that was much more challenging than I expected, but also a lot of fun! The people were great -- the program managers were supportive and highly knowledgeable. The other fellows in my session came from different academic backgrounds, yet we were all able to work together to accomplish very difficult tasks in a short amount of time. If you're interested in transitioning to data science in industry from academia, they are worth a peep. The first few weeks of the fellowship involved putting together data projects which demonstrated our abilities to break out of the academic mindset and focus on finding solutions for practical/everyday or business-related problems. My initial attempt to build a project failed: a cross-art recommendation system. What's that? Basically the idea was that if you have a general interest in fine arts, and really like a certain writer / music