December 2019
Intermediate to advanced
468 pages
14h 28m
English
Content preview from Advanced Deep Learning with Python
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Introduction to GANs
In this section, we'll talk about arguably the most popular generative model today: the GAN framework. It was first introduced in 2014 in the landmark paper Generative Adversarial Nets (http://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf). The GAN framework can work with any type of data, but its most popular application by far is to generate images, and we'll discuss them in this context only. Let's see how it works:
A GAN system
A GAN is a system of two components (neural networks):
- Generator: This is the generative model itself. It takes a probability distribution (random noise) as input and tries to generate ...
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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.