Packt+ | Advance your knowledge in tech

0

All Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Hands-On Natural Language Processing with Python

You're reading from Hands-On Natural Language Processing with Python A practical guide to applying deep learning architectures to your NLP applications

Product type Paperback

Published in Jul 2018

Publisher Packt

ISBN-13 9781789139495

Length 312 pages

Edition 1st Edition

Languages

Processing

Tools

NLTK

Concepts

Deep Learning

Authors (2):

Rajalingappaa Shanmugamani

Rajesh Arumugam

View More author details

Table of Contents (20) Chapters

Title Page

Packt Upsell

Foreword

Contributors

Preface

1. Getting Started

2. Text Classification and POS Tagging Using NLTK FREE CHAPTER

3. Deep Learning and TensorFlow

4. Semantic Embedding Using Shallow Models

5. Text Classification Using LSTM

6. Searching and DeDuplicating Using CNNs

7. Named Entity Recognition Using Character LSTM

8. Text Generation and Summarization Using GRUs

9. Question-Answering and Chatbots Using Memory Networks

10. Machine Translation Using the Attention-Based Model

11. Speech Recognition Using DeepSpeech

12. Text-to-Speech Using Tacotron

13. Deploying Trained Models

1. Other Books You May Enjoy

Leave a review - let other readers know what you think

Index

Chapter 1. Getting Started

Natural language processing (NLP) is the field of understanding human language using computers. It involves the analysis and of large volumes of natural language data using computers to glean meaning and value for consumption in real-world applications. While NLP has been around since the 1950s, there has been tremendous growth in practical applications in the area, due to recent advances in machine learning (ML) and deep learning. The majority of this book will focus on various real-world applications of NLP, such as text classification, and sub-tasks of NLP, such as Named Entity Recognition (NER), with a particular emphasis on deep learning approaches. In this chapter, we will first introduce the basic concepts and terms in NLP. Following this, we will discuss some of the currently used applications that leverage NLP.

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $15.99/month. Cancel anytime

Authors (5)

Shanmugamani

Shanmugamani

Rajalingappaa Shanmugamani is currently working as an Engineering Manager for a Deep learning team at Kairos. Previously, he worked as a Senior Machine Learning Developer at SAP, Singapore and worked at various startups in developing machine learning products. He has a Masters from Indian Institute of TechnologyMadras. He has published articles in peer-reviewed journals and conferences and submitted applications for several patents in the area of machine learning. In his spare time, he coaches programming and machine learning to school students and engineers.

See other products by Shanmugamani

Arumugam

Arumugam

Rajesh Arumugam is an ML developer at SAP, Singapore. Previously, he developed ML solutions for smart city development in areas such as passenger flow analysis in public transit systems and optimization of energy consumption in buildings when working with Centre for Social Innovation at Hitachi Asia, Singapore. He has published papers in conferences and has pending patents in storage and ML. He holds a PhD in computer engineering from Nanyang Technological University, Singapore.

See other products by Arumugam

Byiringiro

Byiringiro

See other products by Byiringiro

Joshi

Joshi

See other products by Joshi

Muthuswamy

Muthuswamy

See other products by Muthuswamy

Other recommended products

Related to this chapter

Hands-On Natural Language Processing with PyTorch 1.x

Hands-On Natural Language Processing with PyTorch 1.x

Developers working with NLP will be able to put their knowledge to work with this practical guide to PyTorch. You will learn to use PyTorch offerings and how to understand and analyze text using Python. You will learn to extract the underlying meaning in the text using deep neural networks and modern deep learning algorithms.

Jul 2020 9h 12m

Advanced Natural Language Processing with TensorFlow 2

Advanced Natural Language Processing with TensorFlow 2

This book provides hands-on training in NLP tools and techniques with intrinsic details. Apart from gaining expertise, you will be able to carry out novel state-of-the-art research using the skills gained.

Feb 2021 12h 40m

Deep Learning for Natural Language Processing

Deep Learning for Natural Language Processing

Starting with the basics, this book teaches you how to choose from the various text pre-processing techniques and select the best model from the several neural network architectures for NLP issues.

Jun 2019 12h 24m

Deep Learning with R Cookbook

Deep Learning with R Cookbook

This book will help you get through the problems that you face during the execution of different tasks and understand hacks in deep learning. With unique recipes, you will implement various deep learning architectures using R 3.5.x. You will cover complex algorithms to perform tasks such as reinforcement learning, GANs, advanced neural networks and more.

Feb 2020 10h 56m

The Natural Language Processing Workshop

The Natural Language Processing Workshop

The Natural Language Processing Workshop takes you through fundamental NLP techniques, such as preparing datasets, collecting text, extracting text, and sentiment analysis. As you progress, you'll get to grips with creating your own chatbots and dynamic models.

Aug 2020 15h 4m

Mastering spaCy

Mastering spaCy

Using machine learning-based NLP models, you can speed up business processes, make more accurate predictions, and uncover new insights from your existing data, where spaCy, an advanced industrial-grade natural language processing library, can help. With this book, you'll learn how to use it and create high-impact ML solutions for NLP.

Jul 2021 11h 52m

Natural Language Processing Fundamentals

Natural Language Processing Fundamentals

Natural Language Processing Fundamentals starts with basics and goes on to explain various NLP tools and techniques that equip you with all that you need to solve common business problems for processing text.

Mar 2019 12h 28m

Recurrent Neural Networks with Python Quick Start Guide

Recurrent Neural Networks with Python Quick Start Guide

Developers struggle to find an easy to follow learning resource for implementing Recurrent Neural Network(RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve the results. This book will teach you the fundamentals of RNNs with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling.

fastText Quick Start Guide

fastText Quick Start Guide

Facebook's fastText library handles text representation and classification, used for Natural Language Processing (NLP). Most organizations have to deal with enormous amounts of text data on a daily basis, and efficient data insights requires powerful NLP tools like fastText. This book is your ideal introduction to fastText.

Jul 2018 6h 28m

Deep Learning for Computer Vision

Deep Learning for Computer Vision

Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision, the science of manipulating and processing images. In this book, you will learn different techniques in deep learning to accomplish tasks related to object classification, object detection, image segmentation, captioning, image generation, and more. You will also explore their application using the popular Python libraries such as TensorFlow and Keras. With practical examples, you will learn to develop Computer Vision applications by leveraging the power of deep learning.

Jan 2018 10h 20m

Hands-On Python Natural Language Processing

Hands-On Python Natural Language Processing

This book provides a blend of both the theoretical and practical aspects of Natural Language Processing (NLP). It covers the concepts essential to develop a thorough understanding of NLP and also delves into a detailed discussion on NLP based use-cases such as language translation, sentiment analysis, etc. Every module covers real-world examples

Jun 2020 10h 32m

Python Natural Language Processing Cookbook

Python Natural Language Processing Cookbook

Leverage your natural language processing skills to make sense of text. With this book, you'll learn fundamental and advanced NLP techniques in Python that will help you to make your data fit for application in a wide variety of industries. You'll also find recipes for overcoming common challenges in implementing NLP pipelines.

Mar 2021 9h 28m