GANs in Action (ePub)
Deep learning with Generative Adversarial Networks
(Sprache: Englisch)
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...
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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.
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.
Autoren-Porträt von Vladimir Bok, Jakub Langr
Vladimir Bok
Bibliographische Angaben
- Autoren: Vladimir Bok , Jakub Langr
- 2019, 240 Seiten, Englisch
- Verlag: Simon + Schuster LLC
- ISBN-10: 1638354235
- ISBN-13: 9781638354239
- Erscheinungsdatum: 09.09.2019
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Dateiformat: ePub
- Größe: 6.03 MB
- Mit Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
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