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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Using residual networks for image recognition
In this section, we're going to see what happens when we train deep networks, which has many layers, probably over 30 or maybe even over 100. Then, we'll present residual networks as a solution for scaling too many layers, along with an architecture example with state-of-the-art accuracy.
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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.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.