Natural Language Processing: Python and NLTK

Nitin Hardeniya, Jacob Perkins, Deepti Chopra, Nisheeth Joshi, Iti Mathur

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商品描述

Learn to build expert NLP and machine learning projects using NLTK and other Python libraries

About This Book

  • Break text down into its component parts for spelling correction, feature extraction, and phrase transformation
  • Work through NLP concepts with simple and easy-to-follow programming recipes
  • Gain insights into the current and budding research topics of NLP

Who This Book Is For

If you are an NLP or machine learning enthusiast and an intermediate Python programmer who wants to quickly master NLTK for natural language processing, then this Learning Path will do you a lot of good. Students of linguistics and semantic/sentiment analysis professionals will find it invaluable.

What You Will Learn

  • The scope of natural language complexity and how they are processed by machines
  • Clean and wrangle text using tokenization and chunking to help you process data better
  • Tokenize text into sentences and sentences into words
  • Classify text and perform sentiment analysis
  • Implement string matching algorithms and normalization techniques
  • Understand and implement the concepts of information retrieval and text summarization
  • Find out how to implement various NLP tasks in Python

In Detail

Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning. The number of human-computer interaction instances are increasing so it's becoming imperative that computers comprehend all major natural languages.

The first NLTK Essentials module is an introduction on how to build systems around NLP, with a focus on how to create a customized tokenizer and parser from scratch. You will learn essential concepts of NLP, be given practical insight into open source tool and libraries available in Python, shown how to analyze social media sites, and be given tools to deal with large scale text. This module also provides a workaround using some of the amazing capabilities of Python libraries such as NLTK, scikit-learn, pandas, and NumPy.

The second Python 3 Text Processing with NLTK 3 Cookbook module teaches you the essential techniques of text and language processing with simple, straightforward examples. This includes organizing text corpora, creating your own custom corpus, text classification with a focus on sentiment analysis, and distributed text processing methods.

The third Mastering Natural Language Processing with Python module will help you become an expert and assist you in creating your own NLP projects using NLTK. You will be guided through model development with machine learning tools, shown how to create training data, and given insight into the best practices for designing and building NLP-based applications using Python.

This Learning Path combines some of the best that Packt has to offer in one complete, curated package and is designed to help you quickly learn text processing with Python and NLTK. It includes content from the following Packt products:

  • NTLK essentials by Nitin Hardeniya
  • Python 3 Text Processing with NLTK 3 Cookbook by Jacob Perkins
  • Mastering Natural Language Processing with Python by Deepti Chopra, Nisheeth Joshi, and Iti Mathur

Style and approach

This comprehensive course creates a smooth learning path that teaches you how to get started with Natural Language Processing using Python and NLTK. You'll learn to create effective NLP and machine learning projects using Python and NLTK.

商品描述(中文翻譯)

學習使用NLTK和其他Python庫來建立專業的NLP和機器學習項目

關於本書
- 將文本拆分為其組成部分,進行拼寫校正、特徵提取和短語轉換
- 通過簡單易懂的編程示例來學習NLP概念
- 瞭解當前和新興的NLP研究主題

本書適合對NLP或機器學習感興趣且具有中級Python編程能力的人士,希望快速掌握NLTK進行自然語言處理的技能。語言學和語義/情感分析專業人士也會發現本書非常有價值。

你將學到什麼
- 自然語言的複雜性範圍以及機器如何處理它們
- 使用分詞和分塊來清理和整理文本,以更好地處理數據
- 將文本分割為句子和句子分割為單詞
- 對文本進行分類和情感分析
- 實現字符串匹配算法和正規化技術
- 理解並實現信息檢索和文本摘要的概念
- 瞭解如何在Python中實現各種NLP任務

詳細內容
自然語言處理是計算語言學和人工智能領域,處理人與計算機之間的交互作用。它提供了計算機和人類之間的無縫交互,並使計算機能夠通過機器學習理解人類語言。人與計算機之間的交互實例數量正在增加,因此計算機理解所有主要自然語言變得至關重要。

第一個NLTK Essentials模塊是一個介紹如何構建NLP系統的入門指南,重點是如何從頭開始創建自定義的分詞器和解析器。你將學習NLP的基本概念,獲得有關Python中可用的開源工具和庫的實用見解,並學習如何分析社交媒體網站,以及處理大規模文本的工具。該模塊還提供了使用NLTK、scikit-learn、pandas和NumPy等Python庫的一些令人驚嘆的功能的解決方案。

第二個Python 3 Text Processing with NLTK 3 Cookbook模塊通過簡單明了的示例教授您文本和語言處理的基本技術。這包括組織文本語料庫,創建自己的自定義語料庫,以情感分析為重點的文本分類,以及分佈式文本處理方法。

第三個Mastering Natural Language Processing with Python模塊將幫助您成為一名專家,並協助您使用NLTK創建自己的NLP項目。您將通過機器學習工具進行模型開發,學習如何創建訓練數據,並獲得設計和構建基於NLP的應用程序的最佳實踐見解。

這個學習路徑將Packt的一些最佳內容結合在一個完整的、精選的包裹中,旨在幫助您快速學習使用Python和NLTK進行文本處理。它包括以下Packt產品的內容:
- 《NTLK Essentials》作者:Nitin Hardeniya
- 《Python 3 Text Processing with NLTK 3 Cookbook》作者:Jacob Perkins
- 《Mastering Natural Language Processing with Python》作者:Deepti Chopra、Nisheeth Joshi和Iti Mathur

風格和方法
這個全面的課程為您創建了一個平滑的學習路徑,教您如何使用Python和NLTK開始自然語言處理。您將學習使用Python和NLTK創建有效的NLP和機器學習項目。