Hands-On Question Answering Systems with Bert: Applications in Neural Networks and Natural Language Processing

Sabharwal, Navin, Agrawal, Amit

Hands-On Question Answering Systems with Bert: Applications in Neural Networks and Natural Language Processing
  • 出版商: Apress
  • 出版日期: 2021-01-13
  • 定價: $1,575
  • 售價: 9.5 折 $1,496
  • 貴賓價: 9.0 折 $1,418
  • 語言: 英文
  • 頁數: 184
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1484266633
  • ISBN-13: 9781484266632
  • 相關分類: 人工智慧、DeepLearning、Text-mining

    • 立即出貨 (庫存=1)

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商品描述

Get hands-on knowledge of how BERT (Bidirectional Encoder Representations from Transformers) can be used to develop question answering (QA) systems by using natural language processing (NLP) and deep learning.

The book begins with an overview of the technology landscape behind BERT. It takes you through the basics of NLP, including natural language understanding with tokenization, stemming, and lemmatization, and bag of words. Next, you'll look at neural networks for NLP starting with its variants such as recurrent neural networks, encoders and decoders, bi-directional encoders and decoders, and transformer models. Along the way, you'll cover word embedding and their types along with the basics of BERT.

After this solid foundation, you'll be ready to take a deep dive into BERT algorithms such as masked language models and next sentence prediction. You'll see different BERT variations followed by a hands-on example of a question answering system.

Hands-on Question Answering Systems with BERT is a good starting point for developers and data scientists who want to develop and design NLP systems using BERT. It provides step-by-step guidance for using BERT.

What You Will Learn

  • Examine the fundamentals of word embeddings
  • Apply neural networks and BERT for various NLP tasks
  • Develop a question-answering system from scratch
  • Train question-answering systems for your own data

Who This Book Is For

AI and machine learning developers and natural language processing developers.

 

商品描述(中文翻譯)

本書將帶領讀者深入了解BERT（Bidirectional Encoder Representations from Transformers）如何應用於自然語言處理（NLP）和深度學習，並開發問答系統。

書籍首先概述了BERT背後的技術背景。接著介紹了NLP的基礎知識，包括使用分詞、詞幹提取和詞形還原進行自然語言理解，以及詞袋模型。然後，您將深入研究NLP中的神經網絡，包括循環神經網絡、編碼器和解碼器、雙向編碼器和解碼器以及Transformer模型。在此過程中，您還將學習詞嵌入及其類型，以及BERT的基礎知識。

在建立了堅實的基礎後，您將深入研究BERT算法，如遮罩語言模型和下一句預測。您將了解不同的BERT變體，並進行實際的問答系統示例。

《使用BERT進行問答系統實踐》是開發人員和數據科學家使用BERT開發和設計NLP系統的良好起點。本書提供了使用BERT的逐步指南。

本書的學習重點包括：

- 深入研究詞嵌入的基礎知識
- 應用神經網絡和BERT進行各種NLP任務
- 從頭開始開發問答系統
- 為自己的數據訓練問答系統

本書適合人群包括AI和機器學習開發人員以及自然語言處理開發人員。

作者簡介

Navin is the chief architect for HCL DryICE Autonomics. He is an innovator, thought leader, author, and consultant in the areas of AI, machine learning, cloud computing, big data analytics, and software product development. He is responsible for IP development and service delivery in the areas of AI and machine learning, automation, AIOPS, public cloud GCP, AWS, and Microsoft Azure. Navin has authored 15+ books in the areas of cloud computing, cognitive virtual agents, IBM Watson, GCP, containers, and microservices.

Amit Agrawal is a senior data scientist and researcher delivering solutions in the fields of AI and machine learning. He is responsible for designing end-to-end solutions and architecture for enterprise products. He has also authored and reviewed books in the area of cognitive virtual assistants.

 

 

作者簡介(中文翻譯)

Navin 是 HCL DryICE Autonomics 的首席架構師。他在人工智慧、機器學習、雲端運算、大數據分析和軟體產品開發等領域是一位創新者、思想領袖、作者和顧問。他負責人工智慧和機器學習、自動化、AIOPS、公有雲 GCP、AWS 和 Microsoft Azure 領域的知識產權開發和服務交付。Navin 在雲端運算、認知虛擬助手、IBM Watson、GCP、容器和微服務等領域撰寫了15本以上的書籍。

Amit Agrawal 是一位高級資料科學家和研究人員，致力於人工智慧和機器學習領域的解決方案。他負責設計企業產品的端到端解決方案和架構。他還在認知虛擬助手領域撰寫和審查了書籍。

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