Deep Learning with Python, 2/e (Paperback)
暫譯: 使用 Python 的深度學習（第二版）

Chollet, François

Deep Learning with Python, 2/e (Paperback)

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商品描述

Printed in full color! Unlock the groundbreaking advances of deep learning with this extensively revised new edition of the bestselling original. Learn directly from the creator of Keras and master practical Python deep learning techniques that are easy to apply in the real world.

In Deep Learning with Python, Second Edition you will learn:

    Deep learning from first principles
    Image classification and image segmentation
    Timeseries forecasting
    Text classification and machine translation
    Text generation, neural style transfer, and image generation
    Full color printing throughout

Deep Learning with Python has taught thousands of readers how to put the full capabilities of deep learning into action. This extensively revised full color second edition introduces deep learning using Python and Keras, and is loaded with insights for both novice and experienced ML practitioners. You’ll learn practical techniques that are easy to apply in the real world, and important theory for perfecting neural networks.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology
Recent innovations in deep learning unlock exciting new software capabilities like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach—even if you have no background in mathematics or data science. This book shows you how to get started.

About the book
Deep Learning with Python, Second Edition introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you’ll build your understanding through intuitive explanations, crisp color illustrations, and clear examples. You’ll quickly pick up the skills you need to start developing deep-learning applications.

What's inside

    Deep learning from first principles
    Image classification and image segmentation
    Time series forecasting
    Text classification and machine translation
    Text generation, neural style transfer, and image generation
    Full color printing throughout

About the reader
For readers with intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required.

商品描述(中文翻譯)

印刷全彩！透過這本廣泛修訂的新版本，解鎖深度學習的突破性進展，這是原版暢銷書的全新修訂版。直接向 Keras 的創建者學習，掌握實用的 Python 深度學習技術，這些技術在現實世界中易於應用。

在《使用 Python 的深度學習（第二版）》中，您將學到：

深度學習的基本原理
圖像分類和圖像分割
時間序列預測
文本分類和機器翻譯
文本生成、神經風格轉換和圖像生成
全彩印刷

《使用 Python 的深度學習》已經教會了成千上萬的讀者如何將深度學習的全部能力付諸實踐。這本廣泛修訂的全彩第二版使用 Python 和 Keras 介紹深度學習，並為新手和經驗豐富的機器學習從業者提供了豐富的見解。您將學到易於在現實世界中應用的實用技術，以及完善神經網絡的重要理論。

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

關於技術
最近在深度學習方面的創新解鎖了令人興奮的新軟體功能，如自動語言翻譯、圖像識別等。深度學習正迅速成為每位軟體開發者必備的知識，而像 Keras 和 TensorFlow 這樣的現代工具使其觸手可及——即使您沒有數學或數據科學的背景。本書將指導您如何入門。

關於本書
《使用 Python 的深度學習（第二版）》使用 Python 和強大的 Keras 庫介紹深度學習領域。在這本修訂和擴展的新版本中，Keras 的創建者 François Chollet 為新手和經驗豐富的機器學習從業者提供了見解。在閱讀本書的過程中，您將通過直觀的解釋、清晰的彩色插圖和明確的範例來建立理解。您將迅速掌握開始開發深度學習應用所需的技能。

內容包括：

深度學習的基本原理
圖像分類和圖像分割
時間序列預測
文本分類和機器翻譯
文本生成、神經風格轉換和圖像生成
全彩印刷

關於讀者
適合具備中級 Python 技能的讀者。無需具備 Keras、TensorFlow 或機器學習的先前經驗。

作者簡介

François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does AI research, with a focus on abstraction and reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.

作者簡介(中文翻譯)

François Chollet 在加州山景城的 Google 從事深度學習工作。他是 Keras 深度學習庫的創建者，也是 TensorFlow 機器學習框架的貢獻者。他還進行人工智慧研究，專注於抽象和推理。他的論文已在該領域的主要會議上發表，包括計算機視覺與模式識別會議 (CVPR)、神經資訊處理系統會議與研討會 (NIPS)、學習表徵國際會議 (ICLR) 等。

目錄大綱

1  What is deep learning?
2 The mathematical building blocks of neural networks
3 Introduction to Keras and TensorFlow
4 Getting started with neural networks: Classification and regression
5 Fundamentals of machine learning
6 The universal workflow of machine learning
7 Working with Keras: A deep dive
8 Introduction to deep learning for computer vision
9 Advanced deep learning for computer vision
10 Deep learning for timeseries
11 Deep learning for text
12 Generative deep learning
13 Best practices for the real world
14 Conclusions

目錄大綱(中文翻譯)

1  What is deep learning?

2 The mathematical building blocks of neural networks

3 Introduction to Keras and TensorFlow

4 Getting started with neural networks: Classification and regression

5 Fundamentals of machine learning

6 The universal workflow of machine learning

7 Working with Keras: A deep dive

8 Introduction to deep learning for computer vision

9 Advanced deep learning for computer vision

10 Deep learning for timeseries

11 Deep learning for text

12 Generative deep learning

13 Best practices for the real world

14 Conclusions

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