Search icon CANCEL
Subscription
0
Cart icon
Cart
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
R Deep Learning Cookbook

You're reading from  R Deep Learning Cookbook

Product type Book
Published in Aug 2017
Publisher Packt
ISBN-13 9781787121089
Pages 288 pages
Edition 1st Edition
Languages
Authors (2):
PKS Prakash PKS Prakash
Profile icon PKS Prakash
Achyutuni Sri Krishna Rao Achyutuni Sri Krishna Rao
Profile icon Achyutuni Sri Krishna Rao
View More author details
Toc

Table of Contents (17) Chapters close

Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Getting Started 2. Deep Learning with R 3. Convolution Neural Network 4. Data Representation Using Autoencoders 5. Generative Models in Deep Learning 6. Recurrent Neural Networks 7. Reinforcement Learning 8. Application of Deep Learning in Text Mining 9. Application of Deep Learning to Signal processing 10. Transfer Learning

Setting up a Restricted Boltzmann machine for Bernoulli distribution input


In this section, let's set up a restricted Boltzmann machine for Bernoulli distributed input data, where each attribute has values ranging from 0 to 1 (equivalent to a probability distribution). The dataset (MNIST) used in this recipe has input data satisfying a Bernoulli distribution.

An RBM comprises of two layers: a visible layer and a hidden layer. The visible layer is an input layer of nodes equal to the number of input attributes. In our case, each image in the MNIST dataset is defined using 784 pixels (28 x 28 size). Hence, our visible layer will have 784 nodes.

On the other hand, the hidden layer is generally user-defined. The hidden layer has a set of binary activated nodes, with each node having a probability of linkage with all other visible nodes. In our case, the hidden layer will have 900 nodes. As an initial step, all the nodes in the visible layer are connected with all the nodes in the hidden layer...

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 €14.99/month. Cancel anytime