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Hands-On Python Natural Language Processing
Hands-On Python Natural Language Processing

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

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Hands-On Python Natural Language Processing

Understanding the Basics of NLP

Natural Language Processing (NLP) is an interdisciplinary area of research aimed at making machines understand and process human languages. It is an evolving field, with a rapid increase in its acceptability and adoption in industry, and its growth is projected to continue. NLP-based applications are everywhere, and chances are that you already interact with an NLP-enabled application regularly (Alexa, Google Translate, chatbots, and so on). The objective of this book is to provide a hands-on learning experience and help you build NLP applications by understanding key NLP concepts. The book lays particular emphasis on Machine Learning (ML)- and Deep Learning (DL)-based applications and also delves into recent advances such as Bidirectional Encoder Representations from Transformers (BERT). We start this journey by providing a brief context of NLP and introduce you to some existing and evolving applications of NLP.

In this chapter, we'll cover the following topics:

  • Programming languages versus natural languages
  • Why should I learn NLP?
  • Current applications of NLP

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Key benefits

  • 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

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.

Who is this book 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.

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
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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 26, 2020
Length: 316 pages
Edition : 1st
Language : English
ISBN-13 : 9781838989590
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Product Details

Publication date : Jun 26, 2020
Length: 316 pages
Edition : 1st
Language : English
ISBN-13 : 9781838989590
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Frequently bought together


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Table of Contents

15 Chapters
Section 1: Introduction Chevron down icon Chevron up icon
Understanding the Basics of NLP Chevron down icon Chevron up icon
NLP Using Python Chevron down icon Chevron up icon
Section 2: Natural Language Representation and Mathematics Chevron down icon Chevron up icon
Building Your NLP Vocabulary Chevron down icon Chevron up icon
Transforming Text into Data Structures Chevron down icon Chevron up icon
Word Embeddings and Distance Measurements for Text Chevron down icon Chevron up icon
Exploring Sentence-, Document-, and Character-Level Embeddings Chevron down icon Chevron up icon
Section 3: NLP and Learning Chevron down icon Chevron up icon
Identifying Patterns in Text Using Machine Learning Chevron down icon Chevron up icon
From Human Neurons to Artificial Neurons for Understanding Text Chevron down icon Chevron up icon
Applying Convolutions to Text Chevron down icon Chevron up icon
Capturing Temporal Relationships in Text Chevron down icon Chevron up icon
State of the Art in NLP Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5
(4 Ratings)
5 star 75%
4 star 0%
3 star 25%
2 star 0%
1 star 0%
S Apr 21, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book starts from the basics of NLP and reaches intermediate levels. I like the various concepts and topics (like CNN, Neural Network) covered in this book.A good balance between theory and practical knowledge.Get your Python caps on and enjoy.
Amazon Verified review Amazon
Hoi Nguyen Apr 17, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
this is a great book, highly recommended.
Amazon Verified review Amazon
Alessio Jun 20, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
interessante e semplice
Amazon Verified review Amazon
Amazon Customer May 23, 2023
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
Having learnt quite a bit of machine learning from great books like Hands-on Machine Learning by Aurelion Geron, I decided to pick up some NLP.This book teaches concepts and provides codes to demonstrate various aspects of NLP, which seemed ok, but after going through 40% of the book, there were no coherent case studies put forth. So I am left with knowledge of disparate pieces that I don't quite know how best to put together for a project.I am putting this book aside and practising with another book - Blueprints for Text Analytics with Python. Just started on that one, and it seems much more promising.
Amazon Verified review Amazon
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