GANs in Action : Deep learning with Generative Adversarial Networks / Jakub Langr, Vladimir Bok.

Format:

Sound recording

Author/Creator:

Langr, Jakub, author.

Bok, Vladimir, author.

Language:

English

Subjects (All):

Machine learning--Technological innovations.

Machine learning.

Artificial intelligence--Computer programs.

Artificial intelligence.

Physical Description:

1 online resource (1 audio file)

Edition:

1st edition.

Other Title:

GANs in Action

Place of Publication:

Shelter Island, New York : Manning Publications, 2021.

Summary:

Generative Adversarial Networks, GANs, are an incredible AI technology capable of creating images, sound, and videos that are indistinguishable from the "real thing". By pitting two neural networks against each other, one to generate fakes and one to spot them, GANs rapidly learn to produce photo-realistic faces and other media objects. With the potential to produce stunningly realistic animations or shocking deepfakes, GANs are a huge step forward in deep learning systems. "GANs in action" teaches you to build and train your own Generative Adversarial Networks. You'll start by creating simple generator and discriminator networks that are the foundation of GAN architecture. Then, following numerous hands-on examples, you'll train GANs to generate high-resolution images, image-to-image translation, and targeted data generation. Along the way, you'll find pro tips for making your system smart, effective, and fast.

Contents:

Introduction to GANs and generative modeling

Advanced topics in GANs

Where to go from here.

Notes:

Description based on: online resource; title from PDF information screen (Manning Publications, viewed February 09, 2023).

Includes bibliographical references and index.

OCLC:

1281680069

Publisher Number:

9781617295560AU