January 2018
Beginner to intermediate
284 pages
8h 35m
English
Content preview from Deep Learning Essentials
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Leaky ReLU and maxout
A Leaky ReLU will have a small slope α on the negative side, such as 0.01. The slope α can also be made into a parameter of each neuron, such as in PReLU neurons (P stands for parametric). The problem with this activation function is the inconsistency of the effectiveness of such modifications to various problems.
Maxout is another attempt to solve the dead neuron problem in ReLU. It takes the form 
. From this form, we can see that both ReLU and leaky ReLU are just special cases of this form, that is, for ReLU, it's 
. Although ...
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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.