Deep Learning with Python, 2/e (Paperback)
Chollet, François
- 出版商: Manning
- 出版日期: 2021-12-21
- 售價: $2,170
- 貴賓價: 9.5 折 $2,062
- 語言: 英文
- 頁數: 504
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1617296864
- ISBN-13: 9781617296864
-
相關分類:
Python、程式語言、DeepLearning
-
相關翻譯:
Keras 大神歸位：深度學習全面進化！用 Python 實作 CNN、RNN、GRU、LSTM、GAN、VAE、Transformer (繁中版)
Python深度學習（第2版） (簡中版)
銷售排行:
👍 2022 年度 英文書 銷售排行 第 19 名
🥈 2022/1 英文書 銷售排行 第 2 名
買這商品的人也買了...
-
Pattern Recognition and Machine Learning (Hardcover)$3,500$3,325 -
$1,617Deep Learning (Hardcover) -
Deep learning 深度學習必讀 - Keras 大神帶你用 Python 實作 (Deep Learning with Python)$1,000$790 -
深度學習 (Deep Learning)(繁體中文版)$1,200$1,020 -
$1,529Introduction to Machine Learning, 4/e (Hardcover) -
$454深度學習與目標檢測 -
Mathematics for Machine Learning (Paperback)$1,480$1,450 -
Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, 2/e (Paperback)$2,622$2,484 -
Mastering Docker, Fourth Edition$1,650$1,568 -
輕鬆學會 Google TensorFlow 2 人工智慧深度學習實作開發, 3/e$620$484 -
Introduction to Computer Graphics with OpenGL ES (Paperback)$2,400$2,280 -
$470計算機視覺中的深度學習 -
Artificial Intelligence: A Modern Approach, 4/e (IE-Paperback)$1,460$1,387 -
$715深度學習實戰：基於 TensorFlow 2 和 Keras, 2/e (Deep Learning with TensorFlow 2 and Keras, 2/e) -
$658Python 深度學習：模型、方法與實現 -
AutoML 自動化機器學習：用 AutoKeras 超輕鬆打造高效能 AI 模型 (Automated Machine Learning with AutoKeras: Deep learning made accessible for everyone with just few lines of coding)$690$587 -
集成式學習：Python 實踐！整合全部技術，打造最強模型 (Hands-On Ensemble Learning with Python: Build highly optimized ensemble machine learning models using scikit-learn and Keras)$750$593 -
Advanced Python Programming : Accelerate your Python programs using proven techniques and design patterns, 2/e (Paperback)$1,800$1,710 -
Probabilistic Machine Learning: An Introduction (Hardcover)$2,650$2,597 -
$2,115Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications (Paperback) -
Keras 大神歸位：深度學習全面進化！用 Python 實作 CNN、RNN、GRU、LSTM、GAN、VAE、Transformer$1,200$1,020 -
Reliable Machine Learning: Applying Sre Principles to ML in Production (Paperback)$2,594$2,457 -
$2,835Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems, 3/e (Paperback) -
從 AI 到 生成式 AI：40個零程式的實作體驗，培養新世代人工智慧素養$560$442 -
精通機器學習｜使用 Scikit-Learn , Keras 與 TensorFlow, 3/e (Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems, 3/e)$1,200$948
相關主題
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)
全彩印刷！通過這本廣受好評的原版書的全面修訂新版，解鎖深度學習的突破性進展。直接向Keras的創作者學習，掌握在現實世界中易於應用的實用Python深度學習技術。
在《Deep Learning with Python, Second Edition》中，您將學習到：
- 從基本原理開始的深度學習
- 圖像分類和圖像分割
- 時序預測
- 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
《Deep Learning with Python》已經教導了成千上萬的讀者如何將深度學習的全部能力應用到實踐中。這本經過廣泛修訂的全彩印刷第二版介紹了使用Python和Keras進行深度學習的知識，並提供了對於初學者和有經驗的機器學習從業者的深入見解。您將學習到在現實世界中易於應用的實用技術，以及完善神經網絡的重要理論。
購買印刷版書籍將包含Manning Publications提供的PDF、Kindle和ePub格式的免費電子書。
關於技術
深度學習的最新創新解鎖了令人興奮的新軟件功能，如自動語言翻譯、圖像識別等。深度學習正迅速成為每個軟件開發人員必備的知識，而現代工具如Keras和TensorFlow使其成為您的選擇，即使您沒有數學或數據科學背景。本書將向您展示如何入門。
關於本書
《Deep Learning with Python, Second Edition》介紹了使用Python和強大的Keras庫進行深度學習的領域。在這本修訂和擴展的新版中，Keras的創作者François Chollet為初學者和有經驗的機器學習從業者提供了見解。通過直觀的解釋、清晰的彩色插圖和明確的示例，您將迅速掌握開發深度學習應用所需的技能。
內容包括：
- 從基本原理開始的深度學習
- 圖像分類和圖像分割
- 時序預測
- 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
適合具有中級Python技能的讀者。不需要之前使用過Keras、TensorFlow或機器學習的經驗。
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 公司從事深度學習的工作。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。他還從事人工智慧研究，專注於抽象和推理。他的論文已在該領域的重要會議上發表，包括計算機視覺和模式識別會議（CVPR）、神經信息處理系統會議和研討會（NIPS）、學習表示國際會議（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 什麼是深度學習？
2 神經網絡的數學基礎
3 Keras和TensorFlow介紹
4 開始使用神經網絡：分類和回歸
5 機器學習的基礎知識
6 機器學習的通用工作流程
7 使用Keras：深入探索
8 視覺計算的深度學習介紹
9 視覺計算的高級深度學習
10 時序數據的深度學習
11 文本的深度學習
12 生成式深度學習
13 實際應用的最佳實踐
14 總結
