GANs in Action: Deep learning with Generative Adversarial Networks teaches you how to build and train your own generative adversarial networks. First, you’ll get an introduction to generative modelling and how GANs work, along with an overview of their potential uses. Then, you’ll start building your own simple adversarial system, as you explore the foundation of GAN architecture: the generator and discriminator networks.
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GANs in Action
1. Deep Learning with
Generative Adversarial
Networks
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2. A leap forward for deep learning
Deep learning systems have gotten
really good identifying patterns in
text, images, and video. But
applications that create realistic
images, natural sentences and
paragraphs, or native-quality
translations have proven elusive.
Enter GANs—Generative Adversarial
Networks.
Where GANs fit into the AI landscape
3. Making AI better
GANs offer a promising solution
to these challenges by pairing
two competing neural
networks—one that generates
content and the other that
rejects samples that are of poor
quality.
And GANs in Action will teach
you how to build and train your
own models!
High-level GAN function diagram
4. Learning first-hand
After getting an
overview of how GANs
work, you’ll dive in and
create and train your
very own GAN, so you
can see the technology
in action.
Because there’s no
better way to learn than
getting in and getting
your hands dirty.
Image generation with GANs
5. Learn from experts
The two authors of GANs in
Action combined have a serious
amount of experience in the field
of data science and in software
engineering.
They have worked at many major
tech companies and have
extensive experience in teaching
data science.
You’re in good hands!
Multivariate 2d distribution
6. If you want to learn more about
the book, you can read the first
chapter of GANs in Action for free
here.
Get GANs in Action for 42% off. Just enter
code sllangr into the discount code box at
manning.com.