Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Apache Spark Deep Learning Cookbook

You're reading from   Apache Spark Deep Learning Cookbook Over 80 best practice recipes for the distributed training and deployment of neural networks using Keras and TensorFlow

Arrow left icon
Product type Paperback
Published in Jul 2018
Publisher Packt
ISBN-13 9781788474221
Length 474 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Ahmed Sherif Ahmed Sherif
Author Profile Icon Ahmed Sherif
Ahmed Sherif
Amrith Ravindra Amrith Ravindra
Author Profile Icon Amrith Ravindra
Amrith Ravindra
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Setting Up Spark for Deep Learning Development FREE CHAPTER 2. Creating a Neural Network in Spark 3. Pain Points of Convolutional Neural Networks 4. Pain Points of Recurrent Neural Networks 5. Predicting Fire Department Calls with Spark ML 6. Using LSTMs in Generative Networks 7. Natural Language Processing with TF-IDF 8. Real Estate Value Prediction Using XGBoost 9. Predicting Apple Stock Market Cost with LSTM 10. Face Recognition Using Deep Convolutional Networks 11. Creating and Visualizing Word Vectors Using Word2Vec 12. Creating a Movie Recommendation Engine with Keras 13. Image Classification with TensorFlow on Spark 14. Other Books You May Enjoy

Introduction to feedforward networks

To understand recurrent networks, first you have to understand the basics of feedforward networks. Both of these networks are named after the way they move information through a series of mathematical operations performed at the nodes of the network. One feeds information in only one direction through every node (never touching a given node twice), while the other cycles it through a loop and feeds it back to the same node (kind of like a feedback loop). It is easily understood how the first kind is called a feedforward network, while the latter is recurrent.

Getting ready

The most important concept while understanding any neural network diagram is the concept of computational graphs...

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 $19.99/month. Cancel anytime
Banner background image