January 2018
Beginner to intermediate
284 pages
8h 35m
English
Content preview from Deep Learning Essentials
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All-zero
First, do NOT use all-zero initialization. Given proper data normalization, it is expected that roughly half of the network weights will be positive and half will be negative. However, this does not mean that weights should be initialized in between, which is zero. Assuming all the weights are the same (no matter if they are zero or not), means that the backpropagation would produce the same result for different parts of the network, which cannot help much in learning.
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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.