Data

DIY DATA SCIENCE, PART 2: M IS FOR MACHINE LEARNING

May 1, 2017
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I’m keeping it short & sweet this week; many of the letters I’ve chosen for this project will focus on machine learning algorithms in more detail, so here’s a tiny visual overview instead. For reference, I’m planning on watching all of these lovely lectures in the future and potentially invest in this book to get a little more grounding in the maths behind machine learning (hello darkness, my old friend).

One of the lovely things about this project is also that there’s no point in being a perfectionist; I won’t be able to produce flawless content every week, so it’s nice to embrace ‘good enough’, mix it up (like this week) and make it a priority to keep going.

On another note, I’m genuinely very, very excited that I get to attend the PyData London conference next weekend. The schedule looks incredible and I can already sense some tricky decisions. Do you spot something I shouldn’t miss? Let me know.

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