Natural Language Processing with AWS AI Services: Derive strategic insights from unstructured data with Amazon Textract and Amazon Comprehend

M, Mona, Rangarajan, Premkumar

  • 出版商: Packt Publishing
  • 出版日期: 2021-11-26
  • 定價: $1,925
  • 售價: 9.0$1,733
  • 語言: 英文
  • 頁數: 512
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1801812535
  • ISBN-13: 9781801812535
  • 相關分類: Amazon Web Services人工智慧
  • 立即出貨 (庫存=1)

相關主題

商品描述

Work through interesting real-life business use cases to uncover valuable insights from unstructured text using AWS AI services


Key Features:

  • Get to grips with AWS AI services for NLP and find out how to use them to gain strategic insights
  • Run Python code to use Amazon Textract and Amazon Comprehend to accelerate business outcomes
  • Understand how you can integrate human-in-the-loop for custom NLP use cases with Amazon A2I

Book Description:

Natural language processing (NLP) uses machine learning to extract information from unstructured data. This book will help you to move quickly from business questions to high-performance models in production.

To start with, you'll understand the importance of NLP in today's business applications and learn the features of Amazon Comprehend and Amazon Textract to build NLP models using Python and Jupyter Notebooks. The book then shows you how to integrate AI in applications for accelerating business outcomes with just a few lines of code. Throughout the book, you'll cover use cases such as smart text search, setting up compliance and controls when processing confidential documents, real-time text analytics, and much more to understand various NLP scenarios. You'll deploy and monitor scalable NLP models in production for real-time and batch requirements. As you advance, you'll explore strategies for including humans in the loop for different purposes in a document processing workflow. Moreover, you'll learn best practices for auto-scaling your NLP inference for enterprise traffic.

Whether you're new to ML or an experienced practitioner, by the end of this NLP book, you'll have the confidence to use AWS AI services to build powerful NLP applications.


What You Will Learn:

  • Automate various NLP workflows on AWS to accelerate business outcomes
  • Use Amazon Textract for text, tables, and handwriting recognition from images and PDF files
  • Gain insights from unstructured text in the form of sentiment analysis, topic modeling, and more using Amazon Comprehend
  • Set up end-to-end document processing pipelines to understand the role of humans in the loop
  • Develop NLP-based intelligent search solutions with just a few lines of code
  • Create both real-time and batch document processing pipelines using Python


Who this book is for:

If you're an NLP developer or data scientist looking to get started with AWS AI services to implement various NLP scenarios quickly, this book is for you. It will show you how easy it is to integrate AI in applications with just a few lines of code. A basic understanding of machine learning (ML) concepts is necessary to understand the concepts covered. Experience with Jupyter notebooks and Python will be helpful.

商品描述(中文翻譯)

這本書的標題是「使用AWS AI服務從非結構化文本中發現有價值的洞察力,並通過有趣的真實商業案例進行實踐」。書中介紹了以下主要特點:
- 瞭解AWS自然語言處理(NLP)服務,並學習如何使用它們獲取戰略洞察力。
- 使用Python代碼運行Amazon Textract和Amazon Comprehend,加速業務成果。
- 了解如何在自定義NLP案例中將人工環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環環