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 By Example

You're reading from   Deep Learning By Example A hands-on guide to implementing advanced machine learning algorithms and neural networks

Arrow left icon
Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788399906
Length 450 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Ahmed Menshawy Ahmed Menshawy
Author Profile Icon Ahmed Menshawy
Ahmed Menshawy
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

Preface 1. Data Science - A Birds' Eye View 2. Data Modeling in Action - The Titanic Example FREE CHAPTER 3. Feature Engineering and Model Complexity – The Titanic Example Revisited 4. Get Up and Running with TensorFlow 5. TensorFlow in Action - Some Basic Examples 6. Deep Feed-forward Neural Networks - Implementing Digit Classification 7. Introduction to Convolutional Neural Networks 8. Object Detection – CIFAR-10 Example 9. Object Detection – Transfer Learning with CNNs 10. Recurrent-Type Neural Networks - Language Modeling 11. Representation Learning - Implementing Word Embeddings 12. Neural Sentiment Analysis 13. Autoencoders – Feature Extraction and Denoising 14. Generative Adversarial Networks 15. Face Generation and Handling Missing Labels 16. Implementing Fish Recognition 17. Other Books You May Enjoy

Deep Feed-forward Neural Networks - Implementing Digit Classification

A feed-forward neural network (FNN) is a special type of neural network wherein links/connections between neurons do not form a cycle. As such, it is different from other architectures in a neural network that we will get to study later on in this book (recurrent-type neural networks). The FNN is a widely used architecture and it was the first and simplest type of neural network.

In this chapter, we will go through the architecture of a typical ;FNN, and we will be using the TensorFlow library for this. After covering these concepts, we will give a practical example of digit classification. The question of this example is, Given a set of images that contain handwritten digits, how can you classify these images into 10 different classes (0-9)?

The following topics will be covered in this chapter:

  • Hidden units...
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 €18.99/month. Cancel anytime