November 2017
Intermediate to advanced
304 pages
6h 58m
English
Content preview from Machine Learning with TensorFlow 1.x
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Actual cats and dogs
We've demonstrated our new tools on the notMNIST dataset, which was helpful as it served to provide a comparison to our earlier simpler network setup. Now, let's progress to a more difficult problem—actual cats and dogs.
We'll utilize the CIFAR-10 dataset. There will be more than just cats and dogs, there are 10 classes—airplanes, automobiles, birds, cats, deer, dogs, frogs, horses, ships, and trucks. Unlike the notMNIST set, there are two major complexities, which are as follows:
- There is far more heterogeneity in the photos, including background scenes
- The photos are color
We have not worked with color datasets before. Luckily, it is not that different from the usual black and white dataset—we will just add another ...
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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.