Abstract
You don’t need to be nervous though. As Deep Learning is still an extension of the neural network, most of what you previously read is applicable. Therefore, you don’t have many additional concepts to learn.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
As addressed in Chapter 2, the single-layer neural network can solve only linearly separable problems.
- 2.
It earned its name as its behavior is similar to that of the rectifier, an electrical element that converts the alternating current into direct current as it cuts out negative voltage.
- 3.
sebastianruder.com/optimizing-gradient-descent/
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2017 Phil Kim
About this chapter
Cite this chapter
Kim, P. (2017). Deep Learning. In: MATLAB Deep Learning. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-2845-6_5
Download citation
DOI: https://doi.org/10.1007/978-1-4842-2845-6_5
Published:
Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-2844-9
Online ISBN: 978-1-4842-2845-6
eBook Packages: Professional and Applied ComputingApress Access BooksProfessional and Applied Computing (R0)