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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.
Procurando Gans in Action: Deep Learning with Generative Adversarial Networks? Aqui você encontra tudo sobre este livro de Jakub Langr, publicado por Manning Publications. Nesta página estão a descrição da obra, os detalhes da edição (276 páginas) e os formatos disponíveis para baixar: pdf, mp3, áudio-livro, kindle. Se você gosta de Livros Internacionais, Computação, Informática e Mídias Digitais, Programação, Algoritmos, explore também outros títulos da mesma categoria no LivrosQualidade. Veja ainda as outras obras de Jakub Langr em nosso catálogo.
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