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taste_analysis.ipynb

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"\n",
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"That was fun.\n",
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"### Release Dates\n",
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"## Release Dates\n",
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"Which era of music do I prefer?"
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"Pretty good fit! I seem to be extra partial to music from about 5 years ago. We'll see whether the present or maybe the further past catches up.\n",
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"### Popularity Contest\n",
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"## Popularity Contest\n",
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"I was happy to find popularity listed as a field in Spotify's track JSON. It's a percentile between 0 and 100, rather than an absolute number of plays. Still, it can be used to give a notion of how hipster I am."
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"Damn, I'm a hipster.\n",
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"### Track Duration\n",
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"## Track Duration\n",
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"Do I prefer long songs or short ones?"
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"cell_type": "markdown",
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"metadata": {},
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"### Musical Features\n",
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"## Musical Features\n",
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"In the interest of understanding user tastes and providing the best possible music recommendations, Spotify has done [some really sophisticated analysis](http://benanne.github.io/2014/08/05/spotify-cnns.html) of actual track content, which has only gotten more extensive in recent years. Music is a time series, but most similarity metrics (and most ML methods generally) require inputs to be vectors, that is: points in some feature-space. So they've transformed the tracks to numerical metrics like Energy and Valence (continuous) and Key (discrete).\n",
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"So it looks like this category is for actual single beats and unusual time signatures that Spotify isn't sure what to do with.\n",
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"### Joint Analysis\n",
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"## Joint Analysis\n",
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"I mostly just want to showcase what's possible. Let's plot Energy and Popularity together to see whether there is a relationship."
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"The density is pretty scattered, doesn't the whole plot, meaning the relationship here is actually pretty weak. Surprising.\n",
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"### The Final Frontier\n",
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"## The Final Frontier\n",
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"Finally, I'm going to follow [this guy's example](https://medium.com/cuepoint/visualizing-hundreds-of-my-favorite-songs-on-spotify-fe50c94b8af3) and feed the dimension-reduced data to a one-class SVM to get a sense of what the frontier of my normal taste looks like in that space, [heat-map-of-the-universe-style](https://www.nasa.gov/mission_pages/planck/multimedia/pia16873.html).\n",
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"\n",

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