In this video, W&B’s Deep Learning Educator Charles Frye covers the core ideas from probability that you need in order to do machine learning.
In particular, we’ll see why mathematically rigorous probability theory is so challenging, and then go over why negative logarithms of probabilities, aka “surprises“, show up so often in machine learning.
Slides here:
Exercise notebooks here:
Check out the other Math4ML videos here
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