More Books:

Generative Deep Learning
Language: en
Pages: 330
Authors: David Foster
Categories: Computers
Type: BOOK - Published: 2019-06-28 - Publisher: "O'Reilly Media, Inc."

Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of
Generatives Deep Learning
Language: de
Pages: 310
Authors: David Foster
Categories: Computers
Type: BOOK - Published: 2020 - Publisher:

Generative Modelle haben sich zu einem der spannendsten Themenbereiche der Künstlichen Intelligenz entwickelt: Mit generativem Deep Learning ist es inzwischen möglich, einer Maschine das Malen, Schreiben oder auch das Komponieren von Musik beizubringen - kreative Fähigkeiten, die bisher dem Menschen vorbehalten waren. Mit diesem praxisnahen Buch können Data Scientists einige
Generative Adversarial Networks with Python
Language: en
Pages: 652
Authors: Jason Brownlee
Categories: Computers
Type: BOOK - Published: 2019-07-11 - Publisher: Machine Learning Mastery

Step-by-step tutorials on generative adversarial networks in python for image synthesis and image translation.
GANs in Action
Language: en
Pages: 276
Authors: Jakub Langr, Vladimir Bok
Categories: Computers
Type: BOOK - Published: 2019-10-07 - Publisher: Manning Publications

Deep learning systems have gotten really great at identifying patterns in text, images, and video. But applications that create realistic images, natural sentences and paragraphs, or native-quality translations have proven elusive. Generative Adversarial Networks, or GANs, offer a promising solution to these challenges by pairing two competing neural networks' one
Hands-On Generative Adversarial Networks with Keras
Language: en
Pages: 272
Authors: Rafael Valle
Categories: Computers
Type: BOOK - Published: 2019-05-03 - Publisher: Packt Publishing Ltd

Develop generative models for a variety of real-world use-cases and deploy them to production Key Features Discover various GAN architectures using Python and Keras library Understand how GAN models function with the help of theoretical and practical examples Apply your learnings to become an active contributor to open source GAN