February 2019
Intermediate to advanced
260 pages
6h 3m
English
Content preview from Hands-On Java Deep Learning for Computer Vision
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Why convolution?
So why is convolution so efficient? In order to see that, let's suppose for a moment that we are not using the convolution layer, but instead, a fully-connected or dense layer:
So, we have the input, 784, which is just a multiplication of 28 x 28, and the first hidden layer or dense layer, which is 11,520. Basically, multiplying the multiplication of the three numbers will give 11,520.
Since this is fully-connected, which means that each of the input, is connected to all of the outputs, it means that for each input, we have 11,500 parameters to learn. In total, that's 9,000,000 parameters to learn. Imagine this is just the ...
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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.