Gans in Action Deep Learning with Generative Adversarial Networks

Langr, Jakub & Vladimir Bok

ISBN 10: 1617295566 / ISBN 13: 9781617295560

Edité par Manning, Shelter Island, NY, 2019

A propos de cet article

7.38 X 0.4 X 9.25 inches; 214 pages; Light rubbing (shelf wear) to covers. Very Good condition otherwise. No other noteworthy defects. No markings. ; - Your satisfaction is our priority. We offer free returns and respond promptly to all inquiries. Your item will be carefully cushioned in bubble wrap and securely boxed. All orders ship on the same or next business day. Buy with confidence.

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Détails bibliographiques

• Titre: Gans in Action Deep Learning with Generative Adversarial Networks
• Éditeur: Manning, Shelter Island, NY
• Date de parution: 2019
• Langue: anglais
• ISBN à 10 chiffres: 1617295566
• ISBN à 13 chiffres: 9781617295560
• Reliure: Paperback
• Édition: 1st Edition (Unstated).
• État de l'article: Very Good-

A propos de ce titre

Synopsis

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 that generates content and the other that rejects samples that are of poor quality.

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.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

À propos des auteurs

Jakub Langr graduated from Oxford University where he also taught at OU Computing Services. He has worked in data science since 2013, most recently as a data science Tech Lead at Filtered.com and as a data science consultant at Mudano. Jakub also designed and teaches Data Science courses at the University of Birmingham and is a fellow of the Royal Statistical Society.

Vladimir Bok is a Senior Product Manager at Intent Media, a data science company for leading travel sites, where he helps oversee the company's Machine Learning research and infrastructure teams. Prior to that, he was a Program Manager at Microsoft. Vladimir graduated Cum Laude with a degree in Computer Science from Harvard University. He has worked as a software engineer at early stage FinTech companies, including one founded by PayPal co-founder Max Levchin, and as a Data Scientist at a Y Combinator startup.