February 2018
Beginner to intermediate
258 pages
5h 47m
English
Content preview from R Deep Learning Projects
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First attempt – logistic regression
We start off with probably the most basic classifier, the logistic regression, to be specific multinomial logistic regression as it is a multiclass case. It is a probabilistic linear classifier parameterized by a weight matrix W (also called coefficient matrix) and a bias (also called intercept) vector b. And it maps an input vector x to a set of probabilities P(y=1), P(y=2),. . ., P(y-K) for K possible classes.
A multinomial logistic regression for two possible classes can be represented graphically as follows:
Suppose x is n-dimension, then the weight matrix W is of size n by K with each column Wk representing ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.