finelybook
Hands-On Python Natural Language Processing: Explore tools and techniques to analyze and process text with a view to building real-world NLP applications
by 作者: Aman Kedia and Mayank Rasu
pages 页数: 316 pages
Publisher Finelybook 出版社: Packt Publishing (26 Jun. 2020)
Language 语言: English
ISBN-10 书号: 1838989595
ISBN-13 书号: 9781838989590
Book Description
Get well-versed with traditional as well as modern natural language processing concepts and techniques
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 作者: 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 作者: 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
