finelybook
Python Natural Language Processing Cookbook: Over 50 recipes to understand,analyze,and generate different texts to implement language processing tasks
by 作者: Zhenya Antić
Publisher Finelybook 出版社: Packt Publishing (19 Mar. 2021)
Language 语言: English
pages 页数: 284 pages
ISBN-10 书号: 1838987312
ISBN-13 书号: 9781838987312
Book Description
Get to grips with real-world NLP problems,such as dependency parsing,information extraction,topic modeling,and text data visualization,with this practical guide
Python is the most widely used language for natural language processing (NLP) thanks to its extensive tools and libraries for analyzing text and extracting computer-usable data. This book will take you through techniques for working with text from the basics such as parsing the parts of speech to complex topics such as topic modeling,text classification,and visualization.
Starting with an overview of NLP,the book presents recipes for dividing text into sentences,stemming and lemmatization,removing stopwords,text classification,and parts of speech tagging to help you to structure your data. You’ll then learn dependency parsing,discover different ways of representing text using BERT,and understand the basic implementation of a semantic search for text classification. As you make progress,you’ll also see how to extract information from text,implement unsupervised and supervised techniques for topic modeling,and perform topic modeling of short texts,such as tweets,to be able to use these later for your projects. Additionally,the book covers developing chatbots,keyword matching,and visualizing text data.
By the end of this NLP book,you’ll be able to work with a powerful set of tools for processing text and extracting different types of data from it,such as sentiment,names,topics,and much more.
What you will learn
Become well-versed with basic and advanced NLP techniques in Python
Find out how to pull structured data from large amounts of unstructured text
Explore different techniques for topic modeling such as K-means,LDA,NMF,and BERT
Work with visualization techniques such as NER,topic modeling,and word clouds for different NLP tools
Build a basic chatbot with keyword matching,clustering,and deep learning
Extract information from text using regular expression techniques and neural network tools
