Hands-On Python Natural Language Processing
- Paperback: 316 pages
- Publisher: WOW! eBook (June 26, 2020)
- Language: English
- ISBN-10: 1838989595
- ISBN-13: 978-1838989590
Hands-On Python Natural Language Processing: 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 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.
- 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
By the end of this Hands-On Python Natural Language Processing 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.