Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying The Natural Language Processing Workshop
  • Table Of Contents Toc
The Natural Language Processing Workshop

The Natural Language Processing Workshop

By : Rohan Chopra , Aniruddha M. Godbole , Nipun Sadvilkar , Muzaffar Bashir Shah , Sohom Ghosh , Dwight Gunning , Ankit Bhatia, Nagendra Nagaraj, John Bura, Sumit Kumar Raj, Tom Taulli, Ankit Verma
4.5 (4)
close
close
The Natural Language Processing Workshop

The Natural Language Processing Workshop

4.5 (4)
By: Rohan Chopra , Aniruddha M. Godbole , Nipun Sadvilkar , Muzaffar Bashir Shah , Sohom Ghosh , Dwight Gunning , Ankit Bhatia, Nagendra Nagaraj, John Bura, Sumit Kumar Raj, Tom Taulli, Ankit Verma

Overview of this book

Do you want to learn how to communicate with computer systems using Natural Language Processing (NLP) techniques, or make a machine understand human sentiments? Do you want to build applications like Siri, Alexa, or chatbots, even if you’ve never done it before? With The Natural Language Processing Workshop, you can expect to make consistent progress as a beginner, and get up to speed in an interactive way, with the help of hands-on activities and fun exercises. The book starts with an introduction to NLP. You’ll study different approaches to NLP tasks, and perform exercises in Python to understand the process of preparing datasets for NLP models. Next, you’ll use advanced NLP algorithms and visualization techniques to collect datasets from open websites, and to summarize and generate random text from a document. In the final chapters, you’ll use NLP to create a chatbot that detects positive or negative sentiment in text documents such as movie reviews. By the end of this book, you’ll be equipped with the essential NLP tools and techniques you need to solve common business problems that involve processing text.
Table of Contents (10 chapters)
close
close
Preface

Introduction

In the previous chapter, we looked at text generation, paraphrasing, and summarization, all of which can be immensely useful in helping us focus on only the essential and meaningful parts of the text corpus. This, in turn, helps us to further refine the results of our NLP project. In this chapter, we will look at sentiment analysis, which, as the name suggests, is the area of NLP that involves teaching computers how to identify the sentiment behind written content or parsed audio—that is, audio converted to text. Adding this ability to automatically detect sentiment in large volumes of text and speech opens new possibilities for us to write useful software.

In sentiment analysis, we try to build models that detect how people feel. This starts with determining what kind of feeling we want to detect. Our application may attempt to determine the level of human emotion (most often, whether a person is sad or happy; satisfied or dissatisfied; or interested or disinterested...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
The Natural Language Processing Workshop
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon