An eclectic Spotify library, visualized with Chartify

I’ve been collecting songs in my Spotify library for a good few years now, so it’s fairly representative of my more recent tastes. After looking for tools to get detailed information on my library for analysis purposes, I ran across this Medium post by Dimitris Spathis on visualization of music tastes gathered from Sort Your Music.

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Creating a soccer team for FIFA 2018 with machine learning

Recently I began working with Kaggle’s datasets and kernel environment for data science, and have found them incredibly useful for quick, self-contained projects and trying out new techniques with Python. Kernels even have version control!

In an effort to branch out of my usual subjects of environment and animal-focused data, I gave myself a challenge: Sports. In this case, specifically soccer. Now, I have no background in soccer, or watching it, or knowing much of anything about it, but I set out to find what was most important in creating a team, and how to communicate player selection evaluation to others creating a team.

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