Natural Language Processing with TensorFlow: The definitive NLP book to implement the most sought-after machine learning models and tasks, 2/e (Paperback)

From introductory NLP tasks to Transformer models, this new edition teaches you to utilize powerful TensorFlow APIs to implement end-to-end NLP solutions driven by performant ML (Machine Learning) models

Key Features:

• Learn to solve common NLP problems effectively with TensorFlow 2.x
• Implement end-to-end data pipelines guided by the underlying ML model architecture
• Use advanced LSTM techniques for complex data transformations, custom models and metrics

Book Description:

Learning how to solve natural language processing (NLP) problems is an important skill to master due to the explosive growth of data combined with the demand for machine learning solutions in production. Natural Language Processing with TensorFlow, Second Edition, will teach you how to solve common real-world NLP problems with a variety of deep learning model architectures.

The book starts by getting readers familiar with NLP and the basics of TensorFlow. Then, it gradually teaches you different facets of TensorFlow 2.x. In the following chapters, you then learn how to generate powerful word vectors, classify text, generate new text, and generate image captions, among other exciting use-cases of real-world NLP.

TensorFlow has evolved to be an ecosystem that supports a machine learning workflow through ingesting and transforming data, building models, monitoring, and productionization. We will then read text directly from files and perform the required transformations through a TensorFlow data pipeline. We will also see how to use a versatile visualization tool known as TensorBoard to visualize our models.

By the end of this NLP book, you will be comfortable with using TensorFlow to build deep learning models with many different architectures, and efficiently ingest data using TensorFlow Additionally, you'll be able to confidently use TensorFlow throughout your machine learning workflow.

What You Will Learn:

• Learn core concepts of NLP and techniques with TensorFlow
• Use statee-of-the-art Transformers and how they are used to solve NLP tasks
• Perform sentence classification and text generation using CNNs and RNNS
• Utilize advanced models for machine translation and image caption generation
• Build end-to-end data pipelines in TensorFlow
• Learn interesting facts and practices related to the task at hand
• Create word representations of large amounts of data for deep learning

Who this book is for:

This book is for Python developers and programmers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks.

Fundamental Python skills are assumed, as well as basic knowledge of machine learning and undergraduate-level calculus and linear algebra. No previous natural language processing experience required.

從介紹性的自然語言處理任務到Transformer模型，這本新版教你如何利用強大的TensorFlow API實現端到端的NLP解決方案，並使用高效的機器學習模型。

主要特點：
- 學習如何有效地使用TensorFlow 2.x解決常見的NLP問題
- 根據底層機器學習模型架構實現端到端的數據流程
- 使用高級LSTM技術進行複雜的數據轉換、自定義模型和指標

書籍描述：
學習如何解決自然語言處理（NLP）問題是一項重要的技能，因為數據的爆炸性增長與對生產中的機器學習解決方案的需求相結合。《TensorFlow自然語言處理第二版》將教你如何使用各種深度學習模型架構解決常見的現實世界NLP問題。

本書首先讓讀者熟悉NLP和TensorFlow的基礎知識，然後逐步教授TensorFlow 2.x的不同方面。在接下來的章節中，你將學習如何生成強大的詞向量、對文本進行分類、生成新的文本和圖像標題等等令人興奮的現實世界NLP應用。

TensorFlow已經發展成一個生態系統，通過對數據進行摄取和轉換、構建模型、監控和生產化來支持機器學習工作流程。我們將直接從文件中讀取文本，並通過TensorFlow數據流程進行所需的轉換。我們還將看到如何使用一個多功能的可視化工具TensorBoard來可視化我們的模型。

通過閱讀本書，你將能夠熟練使用TensorFlow構建具有多種不同架構的深度學習模型，並使用TensorFlow高效地摄取數據。此外，你將能夠自信地在整個機器學習工作流程中使用TensorFlow。

你將學到什麼：
- 學習NLP的核心概念和TensorFlow技術
- 使用最先進的Transformer解決NLP任務
- 使用CNN和RNN進行句子分類和文本生成
- 利用先進的模型進行機器翻譯和圖像標題生成
- 在TensorFlow中構建端到端的數據流程
- 學習與任務相關的有趣事實和實踐
- 為深度學習創建大量數據的詞表示

本書適合對深度學習有濃厚興趣的Python開發人員和程序員，他們想學習如何利用TensorFlow簡化NLP任務。

假設讀者具備基本的Python技能，以及機器學習和本科水平的微積分和線性代數知識。不需要先前的自然語言處理經驗。