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For me, this book's first chapters explained nicely about ML, MAP and Bayesian using real computer vision problems. The author included helpful visual aids (gaussian plots, contour plots, filters output, etc) http://www.computervisionmodels.com

This is a rather unusual book where it gives primer on probabilistic method that is actually applicable in non computer vision problems. It is Bayesian heavy and rarely touches neural networks; the book is released in 2012, the year deep learning boom started.




Yeah, there are lots of good books out there. My goal was to get the point across in a 5-minute read (give or take).




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