Skip to Main Content
Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R
book

Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R

by V Kishore Ayyadevara
June 2018
Intermediate to advanced content levelIntermediate to advanced
379 pages
7h 33m
English
Apress
Content preview from Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R
© V Kishore Ayyadevara 2018
V Kishore AyyadevaraPro Machine Learning Algorithms https://doi.org/10.1007/978-1-4842-3564-5_10

10. Recurrent Neural Network

V Kishore Ayyadevara1 
(1)
Hyderabad, Andhra Pradesh, India
 

In Chapter 9, we looked at how convolutional neural networks (CNNs) improve upon the traditional neural network architecture for image classification. Although CNNs perform very well for image classification in which image translation and rotation are taken care of, they do not necessarily help in identifying temporal patterns. Essentially, one can think of CNNs as identifying static patterns.

Recurrent neural networks (RNNs) are designed to solve the problem of identifying temporal patterns.

In this chapter, you will learn the following: ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Machine Learning Algorithms

Machine Learning Algorithms

Giuseppe Bonaccorso

Publisher Resources

ISBN: 9781484235645Purchase LinkPublisher Website