Advanced Deep Learning with Keras: Applying GANs and other new deep learning algorithms to the real world (Paperback)

Rowel Atienza

  • Advanced Deep Learning with Keras: Applying GANs and other new deep learning algorithms to the real world (Paperback)-preview-1
  • Advanced Deep Learning with Keras: Applying GANs and other new deep learning algorithms to the real world (Paperback)-preview-2
  • Advanced Deep Learning with Keras: Applying GANs and other new deep learning algorithms to the real world (Paperback)-preview-3
  • Advanced Deep Learning with Keras: Applying GANs and other new deep learning algorithms to the real world (Paperback)-preview-4
  • Advanced Deep Learning with Keras: Applying GANs and other new deep learning algorithms to the real world (Paperback)-preview-5
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Advanced Deep Learning with Keras: Applying GANs and other new deep learning algorithms to the real world (Paperback)-preview-1

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商品描述

Understanding and coding advanced deep learning algorithms with the most intuitive deep learning library in existence

Key Features

  • A complete and up-to-date introduction to GANs
  • A complete overview of Keras
  • A dive into advanced deep learning sticking to the essential mathematics

Book Description

Keras enables a new generation of deep learning developers to access the full power of TensorFlow on the one hand, while concentrating on building applications on the other. Even more surprising is the ability to write applications drawing from the power of new algorithms, without actually having to implement all the algorithms, since they are already available.

After introducing Keras and familiarizing the reader with Keras via classical deep learning algorithms, Dr. Atienza walks the developer through autoencoders first. He takes the approach of building on relatively well-known approaches and algorithms, before introducing more recent developments to working developers. He then asks the reader to write and understand an NLP application to prove the practical value of autoencoders written with Keras.

The core of the book lies in the coverage of several classes of adversarial networks (GANs). Dr. Atienza focuses on the most recent successes of GANs and teaches developers to implement newer results for themselves, warning them of pitfalls and showing them the advantages of each. He focuses in particular on Image generation and synthesis.

Finally, the book finishes with an introduction to reinforcement learning, using OpenAI Gym as a framework to simplify experimenting with various policies and algorithms. Again, Keras is the unifying layer through which OpenAI Gym is accessed.

Overall, Advanced Keras shows the full capabilities of Keras to a developer, while trying to avoid looking at underlying infrastructure provided by TensorFlow, Theano or Microsoft Cognitive Services. Dr. Atienza is showing how to get new algorithms to work within Keras, without getting the reader tangled in too many implementation details.

What you will learn

  • You will learn Keras thoroughly
  • To code image synthesis examples with GANs
  • To distinguish various types of adversarial networks and implement them
  • To write a reinforcement learning application with OpenAI gym
  • To step away from classic deep learning and machine learning and write production-ready applications based on recent research

Who This Book Is For

Familiarity with Python and basic machine learning is necessary for this book and it would be preferable if the reader had understood several basic deep learning algorithms, like CNNs and RNNs.

商品描述(中文翻譯)

深入理解並編寫先進的深度學習算法,使用最直觀的深度學習庫

主要特點


  • 全面且最新的 GANs 簡介

  • Keras 的完整概述

  • 深入研究高級深度學習,專注於基本數學

書籍描述

Keras 讓新一代深度學習開發人員一方面可以完全利用 TensorFlow 的強大功能,另一方面又可以專注於構建應用程序。更令人驚訝的是,開發人員可以使用新算法的威力,而無需實現所有算法,因為這些算法已經可用。

在介紹 Keras 並讓讀者熟悉 Keras 的經典深度學習算法後,Atienza 博士首先介紹了自編碼器。他採用了在相對較為熟知的方法和算法的基礎上進一步發展的方法,然後向開發人員介紹了最新的發展。然後,他要求讀者編寫並理解一個 NLP 應用程序,以證明使用 Keras 編寫的自編碼器的實際價值。

本書的核心在於對幾類對抗網絡(GANs)的覆蓋。Atienza 博士專注於 GANs 的最新成功案例,並教導開發人員自己實現更新的結果,同時警告他們可能遇到的問題,並展示每種方法的優勢。他特別關注圖像生成和合成。

最後,本書通過使用 OpenAI Gym 框架來簡化各種策略和算法的實驗,介紹了強化學習。同樣,Keras 是通過它來訪問 OpenAI Gym 的統一層。

總的來說,Advanced Keras 展示了 Keras 對開發人員的全部能力,同時試圖避免涉及 TensorFlow、Theano 或 Microsoft Cognitive Services 提供的底層基礎設施。Atienza 博士展示了如何在 Keras 中使新算法運作,同時避免讀者陷入太多實現細節。

你將學到什麼


  • 全面學習 Keras

  • 使用 GANs 編寫圖像合成示例

  • 區分各種類型的對抗網絡並實現它們

  • 使用 OpenAI Gym 編寫強化學習應用程序

  • 遠離傳統的深度學習和機器學習,根據最新研究編寫基於生產的應用程序

適合閱讀對象

閱讀本書需要熟悉 Python 和基本的機器學習,最好已經理解幾種基本的深度學習算法,如 CNN 和 RNN。