Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Artificial Intelligence for Big Data

You're reading from   Artificial Intelligence for Big Data Complete guide to automating Big Data solutions using Artificial Intelligence techniques

Arrow left icon
Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788472173
Length 384 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Anand Deshpande Anand Deshpande
Author Profile Icon Anand Deshpande
Anand Deshpande
Manish Kumar Manish Kumar
Author Profile Icon Manish Kumar
Manish Kumar
Arrow right icon
View More author details
Toc

Table of Contents (14) Chapters Close

Preface 1. Big Data and Artificial Intelligence Systems FREE CHAPTER 2. Ontology for Big Data 3. Learning from Big Data 4. Neural Network for Big Data 5. Deep Big Data Analytics 6. Natural Language Processing 7. Fuzzy Systems 8. Genetic Programming 9. Swarm Intelligence 10. Reinforcement Learning 11. Cyber Security 12. Cognitive Computing 13. Other Books You May Enjoy

Applying NLP techniques


Generally, for any class of NLP problems, you first apply text preprocessing and feature extraction techniques. Once you have reduced the noise in the text and are able to extract features out of text, you perform various machine learning algorithms to solve different NLP classes of NLP problems. In this section, we will cover one such problem, called text classification.

Text classification

Text classification is one of the very common use cases of NLP. Text classification can be used for use cases such as email SPAM detection, identifying retail product hierarchy, and sentiment analysis. This process is typically a classification problem wherein we are trying to identify a specific topic from a natural language source of a large volume of data. Within each of the data groups, we may have multiple topics discussed and hence it is important to classify the article or the textual information into logical groups. Text classification techniques help us to do that.

These...

lock icon 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
Renews at $19.99/month. Cancel anytime
Banner background image