January 2019
Intermediate to advanced
386 pages
11h 13m
English
book
Python Deep Learning - Second Edition
by Ivan Vasilev, Daniel Slater, Gianmario Spacagna, Peter Roelants, Valentino Zocca
Content preview from Python Deep Learning - Second Edition
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Summary
In this chapter, we discussed how to create new images with generative models, which is one of the most exciting machine learning areas at the moment. We talked about two of the most popular generative algorithms: VAEs and GANs. First, we learned their theoretical foundations and then we implemented simple programs to generate new MNIST digits with each algorithm.
This chapter concludes the series of the last three chapters, which were dedicated to computer vision. In the next chapter, we'll discuss how to apply DL algorithms in the field of natural language processing (NLP). We'll also introduce the main NLP paradigms and a new type of neural network, called the recurrent network, which is especially suited for NLP tasks.
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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.