Hands-On Python Natural Language Processing: Explore tools and techniques to analyze and process text with a view to building real-world NLP applicati

Aman Kedia , Mayank Rasu

  • 出版商: Packt Publishing
  • 出版日期: 2020-06-26
  • 售價: $1,360
  • 貴賓價: 9.5$1,292
  • 語言: 英文
  • 頁數: 316
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1838989595
  • ISBN-13: 9781838989590
  • 相關分類: Python程式語言Text-mining
  • 立即出貨 (庫存=1)

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商品描述

Key Features

  • Perform various NLP tasks to build linguistic applications using Python libraries
  • Understand, analyze, and generate text to provide accurate results
  • Interpret human language using various NLP concepts, methodologies, and tools

Book Description

Natural Language Processing (NLP) is the subfield in computational linguistics that enables computers to understand, process, and analyze text. This book caters to the unmet demand for hands-on training of NLP concepts and provides exposure to real-world applications along with a solid theoretical grounding.

This book starts by introducing you to the field of NLP and its applications, along with the modern Python libraries that you'll use to build your NLP-powered apps. With the help of practical examples, you'll learn how to build reasonably sophisticated NLP applications, and cover various methodologies and challenges in deploying NLP applications in the real world. You'll cover key NLP tasks such as text classification, semantic embedding, sentiment analysis, machine translation, and developing a chatbot using machine learning and deep learning techniques. The book will also help you discover how machine learning techniques play a vital role in making your linguistic apps smart. Every chapter is accompanied by examples of real-world applications to help you build impressive NLP applications of your own.

By the end of this NLP book, you'll be able to work with language data, use machine learning to identify patterns in text, and get acquainted with the advancements in NLP.

What you will learn

  • Understand how NLP powers modern applications
  • Explore key NLP techniques to build your natural language vocabulary
  • Transform text data into mathematical data structures and learn how to improve text mining models
  • Discover how various neural network architectures work with natural language data
  • Get the hang of building sophisticated text processing models using machine learning and deep learning
  • Check out state-of-the-art architectures that have revolutionized research in the NLP domain

Who this book is for

This NLP Python book is for anyone looking to learn NLP's theoretical and practical aspects alike. It starts with the basics and gradually covers advanced concepts to make it easy to follow for readers with varying levels of NLP proficiency. This comprehensive guide will help you develop a thorough understanding of the NLP methodologies for building linguistic applications; however, working knowledge of Python programming language and high school level mathematics is expected.

商品描述(中文翻譯)

主要特點


  • 使用Python庫執行各種自然語言處理(NLP)任務,以構建語言應用程式

  • 理解、分析和生成文本,以提供準確的結果

  • 使用各種NLP概念、方法和工具來解釋人類語言

書籍描述

自然語言處理(NLP)是計算語言學的一個子領域,使計算機能夠理解、處理和分析文本。本書滿足了對NLP概念進行實踐培訓的需求,並提供了實際應用的機會,同時具有堅實的理論基礎。

本書首先介紹了NLP領域及其應用,以及您將用於構建NLP應用程式的現代Python庫。通過實際示例的幫助,您將學習如何構建相當複雜的NLP應用程式,並涵蓋在現實世界中部署NLP應用程式時的各種方法和挑戰。您將涵蓋關鍵的NLP任務,如文本分類、語義嵌入、情感分析、機器翻譯以及使用機器學習和深度學習技術開發聊天機器人。本書還將幫助您了解機器學習技術在使您的語言應用程式智能化方面的重要作用。每一章都附有實際應用示例,以幫助您構建令人印象深刻的自然語言處理應用程式。

通過閱讀本書,您將能夠處理語言數據,使用機器學習識別文本中的模式,並熟悉NLP的最新進展。

您將學到什麼


  • 了解NLP如何驅動現代應用程式

  • 探索關鍵的NLP技術,以構建自然語言詞彙

  • 將文本數據轉換為數學數據結構,並學習如何改進文本挖掘模型

  • 了解各種神經網絡架構如何處理自然語言數據

  • 掌握使用機器學習和深度學習構建複雜文本處理模型的技巧

  • 了解在NLP領域中革命性研究的最新架構

本書適合對象

本書適合任何希望學習NLP理論和實踐方面的人。它從基礎知識開始,逐漸涵蓋高級概念,以便讀者可以根據自己的NLP能力水平進行學習。這本全面的指南將幫助您全面了解構建語言應用程式的NLP方法,但需要具備Python編程語言和高中水平的數學知識。

作者簡介

Aman Kedia is a data enthusiast and lifelong learner. He is an avid believer in Artificial Intelligence (AI) and the algorithms supporting it. He has worked on state-of-the-art problems in Natural Language Processing (NLP), encompassing resume matching and digital assistants, among others. He has worked at Oracle and SAP, trying to solve problems leveraging advancements in AI. He has four published research papers in the domain of AI.

Mayank Rasu has more than 12 years of global experience as a data scientist and quantitative analyst in the investment banking industry. He has worked at the intersection of finance and technology and has developed and deployed AI-based applications within the finance domain. His experience includes building sentiment analyzers, robotics, and deep learning-based document review, among many others areas.

作者簡介(中文翻譯)

Aman Kedia 是一位數據愛好者和終身學習者。他堅信人工智慧(AI)及其支持的算法。他曾在自然語言處理(NLP)領域中從事最先進的問題研究,包括履歷匹配和數字助手等。他曾在 Oracle 和 SAP 工作,嘗試利用人工智慧的進展解決問題。他在人工智慧領域發表了四篇研究論文。

Mayank Rasu 在投資銀行業擁有超過12年的全球經驗,是一位數據科學家和量化分析師。他在金融和技術交叉領域工作,並在金融領域開發和部署基於人工智慧的應用程序。他的經驗包括構建情感分析器、機器人技術和基於深度學習的文件審查等多個領域。

目錄大綱

  1. Understanding the Basics of NLP
  2. NLP Using Python
  3. Building your NLP Vocabulary
  4. Transforming Text into Data Structures
  5. Word Embeddings and Distance Measurements for Text
  6. Exploring Sentence-, Document-, and Character-Level Embeddings
  7. Identifying Patterns in Text using Machine Learning
  8. From Human Neurons to Artificial Neurons for Understanding Text
  9. Applying Convolutions to Text
  10. Capturing Temportal Relationships in Text
  11. State of the Art in NLP

目錄大綱(中文翻譯)

1. 理解自然語言處理的基礎
2. 使用Python進行自然語言處理
3. 建立自然語言處理詞彙
4. 將文本轉換為數據結構
5. 文本的詞嵌入和距離測量
6. 探索句子、文件和字符級別的詞嵌入
7. 使用機器學習識別文本中的模式
8. 從人類神經元到理解文本的人工神經元
9. 將卷積應用於文本
10. 捕捉文本中的時間關係
11. 自然語言處理的最新技術水平