In my last post, I set the stage for this series on using Machine Learning to optimize predictions for the NHL Draft. Specifically, I’ll be concentrating on a dataset of 559 CHL forwards from 1996-2010 over 57 different variables. We ended here: I created the above plot using t-SNE to reduce my dimensions from 57…
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Machine Learning the Draft: Part 1
Hi, internet friends. It’s been awhile! There’s been lots of things happening in Parkatti-land since the last time I looked at hockey stats a few years ago. I’ve furthered my career in analytics, started a family, talked the dog out of mounting young children (for the most part). Honestly, I haven’t watched too many Oiler…