Search icon
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Hands-On Mathematics for Deep Learning

You're reading from  Hands-On Mathematics for Deep Learning

Product type Book
Published in Jun 2020
Publisher Packt
ISBN-13 9781838647292
Pages 364 pages
Edition 1st Edition
Languages
Author (1):
Jay Dawani Jay Dawani
Profile icon Jay Dawani

Table of Contents (19) Chapters

Preface 1. Section 1: Essential Mathematics for Deep Learning
2. Linear Algebra 3. Vector Calculus 4. Probability and Statistics 5. Optimization 6. Graph Theory 7. Section 2: Essential Neural Networks
8. Linear Neural Networks 9. Feedforward Neural Networks 10. Regularization 11. Convolutional Neural Networks 12. Recurrent Neural Networks 13. Section 3: Advanced Deep Learning Concepts Simplified
14. Attention Mechanisms 15. Generative Models 16. Transfer and Meta Learning 17. Geometric Deep Learning 18. Other Books You May Enjoy

Working with the ConvNet architecture

Now that we know all the different components that make up a ConvNet, we can put it all together and see how to construct a deep CNN. In this section, we will build a full architecture and observe how forward propagation works and how we decide the depth of the network, the number of kernels to apply, when and why to use pooling, and so on. But before we dive in, let's explore some of the ways in which CNNs differ from FNNs. They are as follows:

  • The neurons in CNNs have local connectivity, which means that each neuron in a successive layer receives input from a small local group of pixels from an image, instead of receiving the entire image, as a feedforward neural network (FNN) would.
  • Each neuron in the layer of a CNN has the same weight parameters.
  • The layers in CNNs can be normalized.
  • CNNs are translation invariant, which allows us...
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 £13.99/month. Cancel anytime}