GANs in Action: Deep learning with Generative Adversarial Networks (Paperback) Deep learning with Generative Adversarial Networks
暫譯: 《對抗生成網路實戰：深度學習與GANs》

Jakub Langr, Vladimir Bok

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

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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本、圖像和視頻中的模式方面已經變得非常出色。然而，創建逼真的圖像、自然的句子和段落，或本地質量的翻譯的應用仍然難以實現。生成對抗網絡（Generative Adversarial Networks，簡稱 GANs）為這些挑戰提供了一個有前景的解決方案，通過配對兩個競爭的神經網絡：一個生成內容，另一個則拒絕質量不佳的樣本。

《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，你將了解生成建模及 GANs 的工作原理，並概述它們的潛在用途。接著，你將開始構建自己的簡單對抗系統，探索 GAN 架構的基礎：生成器和判別器網絡。

購買印刷版書籍可獲得 Manning Publications 提供的免費電子書，格式包括 PDF、Kindle 和 ePub。

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