Tensorflow in Action

Ganegedara, Thushan

  • 出版商: Manning
  • 出版日期: 2022-10-03
  • 定價: $2,100
  • 售價: 8.0$1,680 (限時優惠至 2024-04-28)
  • 語言: 英文
  • 頁數: 680
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1617298344
  • ISBN-13: 9781617298349
  • 相關分類: DeepLearningTensorFlow
  • 立即出貨

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商品描述

Unlock the TensorFlow design secrets behind successful deep learning applications! Deep learning StackOverflow contributor Thushan Ganegedara teaches you the new features of TensorFlow 2 in this hands-on guide.

In TensorFlow in Action you will learn:

Fundamentals of TensorFlow
Implementing deep learning networks
Picking a high-level Keras API for model building with confidence
Writing comprehensive end-to-end data pipelines
Building models for computer vision and natural language processing
Utilizing pretrained NLP models
Recent algorithms including transformers, attention models, and ElMo

In TensorFlow in Action, you'll dig into the newest version of Google's amazing TensorFlow framework as you learn to create incredible deep learning applications. Author Thushan Ganegedara uses quirky stories, practical examples, and behind-the-scenes explanations to demystify concepts otherwise trapped in dense academic papers. As you dive into modern deep learning techniques like transformer and attention models, you'll benefit from the unique insights of a top StackOverflow contributor for deep learning and NLP.

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

About the technology
Google's TensorFlow framework sits at the heart of modern deep learning. Boasting practical features like multi-GPU support, network data visualization, and easy production pipelines using TensorFlow Extended (TFX), TensorFlow provides the most efficient path to professional AI applications. And the Keras library, fully integrated into TensorFlow 2, makes it a snap to build and train even complex models for vision, language, and more.

About the book
TensorFlow in Action teaches you to construct, train, and deploy deep learning models using TensorFlow 2. In this practical tutorial, you'll build reusable skill hands-on as you create production-ready applications such as a French-to-English translator and a neural network that can write fiction. You'll appreciate the in-depth explanations that go from DL basics to advanced applications in NLP, image processing, and MLOps, complete with important details that you'll return to reference over and over.

What's inside

Covers TensorFlow 2.9
Recent algorithms including transformers, attention models, and ElMo
Build on pretrained models
Writing end-to-end data pipelines with TFX

About the reader
For Python programmers with basic deep learning skills.

About the author
Thushan Ganegedara is a senior ML engineer at Canva and TensorFlow expert. He holds a PhD in machine learning from the University of Sydney.

Table of Contents
PART 1 FOUNDATIONS OF TENSORFLOW 2 AND DEEP LEARNING
1 The amazing world of TensorFlow
2 TensorFlow 2
3 Keras and data retrieval in TensorFlow 2
4 Dipping toes in deep learning
5 State-of-the-art in deep learning: Transformers
PART 2 LOOK MA, NO HANDS! DEEP NETWORKS IN THE REAL WORLD
6 Teaching machines to see: Image classification with CNNs
7 Teaching machines to see better: Improving CNNs and making them confess
8 Telling things apart: Image segmentation
9 Natural language processing with TensorFlow: Sentiment analysis
10 Natural language processing with TensorFlow: Language modeling
PART 3 ADVANCED DEEP NETWORKS FOR COMPLEX PROBLEMS
11 Sequence-to-sequence learning: Part 1
12 Sequence-to-sequence learning: Part 2
13 Transformers
14 TensorBoard: Big brother of TensorFlow
15 TFX: MLOps and deploying models with TensorFlow

商品描述(中文翻譯)

解鎖成功的深度學習應用背後的TensorFlow設計秘訣!深度學習StackOverflow貢獻者Thushan Ganegedara在這本實踐指南中教授您TensorFlow 2的新功能。

在《TensorFlow實戰》中,您將學到:
- TensorFlow的基礎知識
- 實現深度學習網絡
- 選擇高級Keras API自信地構建模型
- 編寫全面的端到端數據流程
- 構建計算機視覺和自然語言處理模型
- 利用預訓練的NLP模型
- 包括Transformer、注意力模型和ElMo在內的最新算法

在《TensorFlow實戰》中,您將深入研究Google令人驚嘆的TensorFlow框架的最新版本,並學習創建令人驚嘆的深度學習應用程序。作者Thushan Ganegedara使用奇特的故事、實用的例子和幕後解釋來揭開原本僅存在於密集學術論文中的概念的神秘面紗。當您深入研究像Transformer和注意力模型等現代深度學習技術時,您將受益於頂級StackOverflow深度學習和NLP貢獻者的獨特見解。

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:
Google的TensorFlow框架是現代深度學習的核心。TensorFlow具有實用的功能,如多GPU支持、網絡數據可視化以及使用TensorFlow Extended(TFX)輕鬆構建生產流程,為專業的AI應用提供了最高效的途徑。而完全集成到TensorFlow 2中的Keras庫使得構建和訓練視覺、語言等複雜模型變得輕而易舉。

關於本書:
《TensorFlow實戰》教您使用TensorFlow 2構建、訓練和部署深度學習模型。在這本實用教程中,您將通過創建可用於生產的應用程序(如法英翻譯器和能夠寫小說的神經網絡)來建立可重用的技能。您將從深度學習基礎知識到NLP、圖像處理和MLOps的高級應用程序的深入解釋中受益,其中包含您將一再參考的重要細節。

內容包括:
- TensorFlow 2.9
- 包括Transformer、注意力模型和ElMo在內的最新算法
- 基於預訓練模型構建
- 使用TFX編寫端到端數據流程

讀者:
適合具備基本深度學習技能的Python程序員。

關於作者:
Thushan Ganegedara是Canva的高級機器學習工程師和TensorFlow專家。他擁有悉尼大學的機器學習博士學位。

目錄:
第1部分 TensorFlow 2和深度學習的基礎
1 TensorFlow的奇妙世界
2 TensorFlow 2
3 TensorFlow 2中的Keras和數據檢索
4 深度學習的初體驗
5 深度學習的最新技術:Transformer

第2部分 看,沒有手!現實世界中的深度網絡
6 教機器看:使用CNN進行圖像分類
7 教機器更好地看:改進CNN並使其坦白
8 區分事物:圖像分割
9 TensorFlow中的自然語言處理:情感分析
10 TensorFlow中的自然語言處理:語言建模

第3部分 複雜問題的高級深度網絡
11 序列到序列學習:第1部分
12 序列到序列學習:第2部分
13 Transformer
14 TensorBoard:TensorFlow的大哥
15 TFX:使用TensorFlow部署模型的MLOps

作者簡介

Thushan Ganegedara is a data scientist with QBE. He holds a PhD in machine learning from the University of Sydney and he has worked with TensorFlow for almost 5 years. Thushan is also one of the most active answer providers for TensorFlow and TensorFlow2.0 tags on Stackoverflow, a DataCamp instructor, and has authored a book and video course on NLP with TensorFlow.

作者簡介(中文翻譯)

Thushan Ganegedara是QBE的資料科學家。他擁有悉尼大學的機器學習博士學位,並且已經使用TensorFlow工作了近5年。Thushan也是Stackoverflow上TensorFlow和TensorFlow2.0標籤中最活躍的解答提供者之一,他還是DataCamp的講師,並且撰寫了一本關於使用TensorFlow進行自然語言處理的書籍和視頻課程。