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Pattern Recognition and Machine Learning (Information Science and Statistics) by
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Evan
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Textbook for information theory and machine learning courses.
— Aug 26, 2016 09:05AM
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Alexis
is on page 127 of 738
Not gonna lie , I gave up on chapter 2 and just read the slides here instead http://lear.inrialpes.fr/~jegou/bisho... which has the cliff notes and useful graphs from the textbook. Good overview of parametric vs nonparameteric methods for density estimation. Intro to common probability distribution functions. My favorite concepts are Gaussian mixture models and Kernal density estimators.
— Jul 15, 2016 04:30AM
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Alexis
is on page 78 of 738
2.3 is dense! I'm not sure if I want to study the entire derivation of Gaussian distribution. The first 8 minutes of this video on Gaussian distribution seems to cover the important properties https://www.youtube.com/watch?v=50Vgw... Will attempt to read it after 2.4
— Jul 09, 2016 05:25AM
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