Search icon CANCEL
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
Deep Learning for Natural Language Processing

You're reading from   Deep Learning for Natural Language Processing Solve your natural language processing problems with smart deep neural networks

Arrow left icon
Product type Paperback
Published in Jun 2019
Publisher
ISBN-13 9781838550295
Length 372 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (4):
Arrow left icon
Karthiek Reddy Bokka Karthiek Reddy Bokka
Author Profile Icon Karthiek Reddy Bokka
Karthiek Reddy Bokka
Monicah Wambugu Monicah Wambugu
Author Profile Icon Monicah Wambugu
Monicah Wambugu
Tanuj Jain Tanuj Jain
Author Profile Icon Tanuj Jain
Tanuj Jain
Shubhangi Hora Shubhangi Hora
Author Profile Icon Shubhangi Hora
Shubhangi Hora
Arrow right icon
View More author details
Toc

Table of Contents (11) Chapters Close

About the Book 1. Introduction to Natural Language Processing FREE CHAPTER 2. Applications of Natural Language Processing 3. Introduction to Neural Networks 4. Foundations of Convolutional Neural Network 5. Recurrent Neural Networks 6. Gated Recurrent Units (GRUs) 7. Long Short-Term Memory (LSTM) 8. State-of-the-Art Natural Language Processing 9. A Practical NLP Project Workflow in an Organization 1. Appendix

Neural Networks

Often neural networks and deep learning are terms that are used interchangeably. They do not mean the same thing, however, so let's learn the difference.

As mentioned before, deep learning is an approach that follows the same principle as machine learning, but does so with more accuracy and efficiency. Deep learning systems make use of artificial neural networks, which are computing models on their own. So, basically, neural networks are a part of the deep learning approach but are not the deep learning approach on their own. They are frameworks that are incorporated by deep learning methods.

Fig 3.2: Neural Networks as a part of the deep learning Approach

Artificial neural networks are based on a framework inspired by the biological neural networks found in the human brain. These neural networks are made of nodes that enable the networks to learn from images, text, real-life objects, and other things, to be able to execute tasks and predict things accuracy...

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