GANs in Action: Deep learning with Generative Adversarial Networks (Paperback) Deep learning with Generative Adversarial Networks

Jakub Langr, Vladimir Bok

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商品描述

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.

商品描述(中文翻譯)

深度學習系統在識別文字、圖像和視頻中的模式方面取得了巨大的進展。但是,創建逼真圖像、自然句子和段落,或者達到母語質量的翻譯的應用一直難以實現。生成對抗網絡(GANs)通過將兩個競爭的神經網絡配對,一個生成內容,另一個拒絕質量差的樣本,為這些挑戰提供了一個有希望的解決方案。

《GANs in Action: Deep learning with Generative Adversarial Networks》教你如何構建和訓練自己的生成對抗網絡。首先,你將介紹生成建模和GANs的工作原理,以及它們的潛在用途概述。然後,你將開始構建自己的簡單對抗系統,同時探索GAN架構的基礎:生成器和鑑別器網絡。

購買印刷版書籍將包含一本免費的電子書(PDF、Kindle和ePub格式),由Manning Publications提供。