Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Natural Language Processing Fundamentals
Natural Language Processing Fundamentals

Natural Language Processing Fundamentals: Build intelligent applications that can interpret the human language to deliver impactful results

Arrow left icon
Profile Icon Sohom Ghosh Profile Icon Dwight Gunning
Arrow right icon
€8.99 €25.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.4 (41 Ratings)
eBook Mar 2019 374 pages 1st Edition
eBook
€8.99 €25.99
Paperback
€32.99
Subscription
Free Trial
Renews at €18.99p/m
Arrow left icon
Profile Icon Sohom Ghosh Profile Icon Dwight Gunning
Arrow right icon
€8.99 €25.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.4 (41 Ratings)
eBook Mar 2019 374 pages 1st Edition
eBook
€8.99 €25.99
Paperback
€32.99
Subscription
Free Trial
Renews at €18.99p/m
eBook
€8.99 €25.99
Paperback
€32.99
Subscription
Free Trial
Renews at €18.99p/m

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Product feature icon AI Assistant (beta) to help accelerate your learning
OR
Modal Close icon
Payment Processing...
tick Completed

Billing Address

Table of content icon View table of contents Preview book icon Preview Book

Natural Language Processing Fundamentals

2. Basic Feature Extraction Methods

Learning Objectives

By the end of this chapter, you will be able to:

  • Categorize data based on content and structure
  • Describe pre-processing steps in detail and implement them to clean text data
  • Describe feature engineering
  • Calculate the similarity between texts
  • Visualize text using word clouds and other visualization techniques

In this chapter, you will learn about basic feature extraction methods in detail and also visualize text with the help of word clouds and other visualization techniques.

Introduction

In the previous chapter, we learned about the concepts of Natural Language Processing (NLP) and text analytics. We also looked at various pre-processing steps in brief. In this chapter, we will learn how to deal with text data whose formats are mostly unstructured. Unstructured data cannot be represented in a tabular format. Therefore, it is essential to convert it into numeric features because most machine learning algorithms are capable of dealing only with numbers. More emphasis will be put on steps such as tokenization, stemming, lemmatization, and stop-word removal. You will also learn about two popular methods for feature extraction: bag of words and Term Frequency-Inverse Document Frequency, as well as various methods for creating new features from existing features. Finally, you will become familiar with how text data can be visualized.

Types of Data

To deal with data effectively, we need to understand the various forms in which it exists. Let's first understand the types of data that exist. There are two main ways to categorize data, by structure and by content, as explained in the upcoming sections.

Categorizing Data Based on Structure

On the basis of structure, data can be divided into three categories, namely structured, semi-structured, and unstructured, as shown in the following diagram:

Figure 2.1: Categorization based on content

These three categories are explained in detail here:

  • Structured Data: This is the most organized form of data. It is represented in tabular formats such as Excel files and Comma-Separated Value (CSV) files. The following figure shows what structured data usually looks like:
Figure 2.2: Structured data
  • Semi-Structured Data: This type of data is not presented in a tabular structure, but it can be represented...

Cleaning Text Data

Most of the time, text data cannot be used as it is. This is because the presence of various unknown symbols or links makes it dirty or unfit for use. Data cleaning is the art of extracting meaningful portions from data by eliminating unnecessary details. Consider the sentence, He tweeted, 'Live coverage of General Elections available at this.tv/show/ge2019. _/\_ Please tune in :) '.

Various symbols, such as "_/\_" and ":)," are present in the sentence. They do not contribute much to its meaning. We need to remove such unwanted details. This is done not only to focus more on the actual content but also to reduce computations. To achieve this, methods such as tokenization and stemming are used. We will learn about them one by one in the upcoming sections.

Tokenization

Tokenization and word tokenizers were briefly described in Chapter 1, Introduction to Natural Language Processing. Tokenization is the process of splitting sentences...

Left arrow icon Right arrow icon

Key benefits

  • Assimilate key NLP concepts and terminologies
  • Explore popular NLP tools and techniques
  • Gain practical experience using NLP in application code

Description

If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems. You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language.

Who is this book for?

Natural Language Processing Fundamentals is designed for novice and mid-level data scientists and machine learning developers who want to gather and analyze text data to build an NLP-powered product. It'll help you to have prior experience of coding in Python using data types, writing functions, and importing libraries. Some experience with linguistics and probability is useful but not necessary.

What you will learn

  • Obtain, verify, and clean data before transforming it into a correct format for use
  • Perform data analysis and machine learning tasks using Python
  • Understand the basics of computational linguistics
  • Build models for general natural language processing tasks
  • Evaluate the performance of a model with the right metrics
  • Visualize, quantify, and perform exploratory analysis from any text data

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 30, 2019
Length: 374 pages
Edition : 1st
Language : English
ISBN-13 : 9781789955989
Category :
Languages :
Tools :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Product feature icon AI Assistant (beta) to help accelerate your learning
OR
Modal Close icon
Payment Processing...
tick Completed

Billing Address

Product Details

Publication date : Mar 30, 2019
Length: 374 pages
Edition : 1st
Language : English
ISBN-13 : 9781789955989
Category :
Languages :
Tools :

Packt Subscriptions

See our plans and pricing
Modal Close icon
€18.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
€189.99 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just €5 each
Feature tick icon Exclusive print discounts
€264.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just €5 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total 95.97
Deep Learning for Natural Language Processing
€29.99
Hands-On Natural Language Processing with Python
€32.99
Natural Language Processing Fundamentals
€32.99
Total 95.97 Stars icon
Banner background image

Table of Contents

8 Chapters
1. Introduction to Natural Language Processing Chevron down icon Chevron up icon
2. Basic Feature Extraction Methods Chevron down icon Chevron up icon
3. Developing a Text classifier Chevron down icon Chevron up icon
4. Collecting Text Data from the Web Chevron down icon Chevron up icon
5. Topic Modeling Chevron down icon Chevron up icon
6. Text Summarization and Text Generation Chevron down icon Chevron up icon
7. Vector Representation Chevron down icon Chevron up icon
8. Sentiment Analysis Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.4
(41 Ratings)
5 star 56.1%
4 star 29.3%
3 star 12.2%
2 star 2.4%
1 star 0%
Filter icon Filter
Top Reviews

Filter reviews by




TD59 Jun 20, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
As an NLP practitioner, I recommend this book. It includes all the key topics of NLP, clearly explained and supported by exercises. The book provides a great introduction to this important area of Artificial Intelligence.
Amazon Verified review Amazon
Arunachala Damodar Dec 09, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
A hidden gem, not many look into this. Guys, NLP is here!!!
Udemy Verified review Udemy
Ramon Domingues Oct 15, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Udemy Verified review Udemy
Surya Prabha Vallae Aug 30, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Udemy Verified review Udemy
Louis Rewiako Aug 21, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great and really comprehensive
Udemy Verified review Udemy
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

How do I buy and download an eBook? Chevron down icon Chevron up icon

Where there is an eBook version of a title available, you can buy it from the book details for that title. Add either the standalone eBook or the eBook and print book bundle to your shopping cart. Your eBook will show in your cart as a product on its own. After completing checkout and payment in the normal way, you will receive your receipt on the screen containing a link to a personalised PDF download file. This link will remain active for 30 days. You can download backup copies of the file by logging in to your account at any time.

If you already have Adobe reader installed, then clicking on the link will download and open the PDF file directly. If you don't, then save the PDF file on your machine and download the Reader to view it.

Please Note: Packt eBooks are non-returnable and non-refundable.

Packt eBook and Licensing When you buy an eBook from Packt Publishing, completing your purchase means you accept the terms of our licence agreement. Please read the full text of the agreement. In it we have tried to balance the need for the ebook to be usable for you the reader with our needs to protect the rights of us as Publishers and of our authors. In summary, the agreement says:

  • You may make copies of your eBook for your own use onto any machine
  • You may not pass copies of the eBook on to anyone else
How can I make a purchase on your website? Chevron down icon Chevron up icon

If you want to purchase a video course, eBook or Bundle (Print+eBook) please follow below steps:

  1. Register on our website using your email address and the password.
  2. Search for the title by name or ISBN using the search option.
  3. Select the title you want to purchase.
  4. Choose the format you wish to purchase the title in; if you order the Print Book, you get a free eBook copy of the same title. 
  5. Proceed with the checkout process (payment to be made using Credit Card, Debit Cart, or PayPal)
Where can I access support around an eBook? Chevron down icon Chevron up icon
  • If you experience a problem with using or installing Adobe Reader, the contact Adobe directly.
  • To view the errata for the book, see www.packtpub.com/support and view the pages for the title you have.
  • To view your account details or to download a new copy of the book go to www.packtpub.com/account
  • To contact us directly if a problem is not resolved, use www.packtpub.com/contact-us
What eBook formats do Packt support? Chevron down icon Chevron up icon

Our eBooks are currently available in a variety of formats such as PDF and ePubs. In the future, this may well change with trends and development in technology, but please note that our PDFs are not Adobe eBook Reader format, which has greater restrictions on security.

You will need to use Adobe Reader v9 or later in order to read Packt's PDF eBooks.

What are the benefits of eBooks? Chevron down icon Chevron up icon
  • You can get the information you need immediately
  • You can easily take them with you on a laptop
  • You can download them an unlimited number of times
  • You can print them out
  • They are copy-paste enabled
  • They are searchable
  • There is no password protection
  • They are lower price than print
  • They save resources and space
What is an eBook? Chevron down icon Chevron up icon

Packt eBooks are a complete electronic version of the print edition, available in PDF and ePub formats. Every piece of content down to the page numbering is the same. Because we save the costs of printing and shipping the book to you, we are able to offer eBooks at a lower cost than print editions.

When you have purchased an eBook, simply login to your account and click on the link in Your Download Area. We recommend you saving the file to your hard drive before opening it.

For optimal viewing of our eBooks, we recommend you download and install the free Adobe Reader version 9.