Skip to Main Content
The Deep Learning with Keras Workshop
book

The Deep Learning with Keras Workshop

by Matthew Moocarme, Mahla Abdolahnejad, Ritesh Bhagwat
July 2020
Intermediate to advanced content levelIntermediate to advanced
496 pages
9h 10m
English
Packt Publishing
Content preview from The Deep Learning with Keras Workshop

9. Sequential Modeling with Recurrent Neural Networks

Overview

This chapter will introduce you to sequential modeling—creating models to predict the next value or series of values in a sequence. By the end of this chapter, you will be able to build sequential models, explain Recurrent Neural Networks (RNNs), describe the vanishing gradient problem, and implement Long Short-Term Memory (LSTM) architectures. You will apply RNNs with LSTM architectures to predict the value of the future stock price value of Alphabet and Amazon.

Introduction

In the previous chapter, we learned about pre-trained networks and how to utilize them for our own applications via transfer learning. We experimented with VGG16 and ResNet50, two pre-trained networks ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

The Applied TensorFlow and Keras Workshop

The Applied TensorFlow and Keras Workshop

Harveen Singh Chadha, Luis Capelo
Keras 2.x Projects

Keras 2.x Projects

Giuseppe Ciaburro
Trends in Deep Learning Methodologies

Trends in Deep Learning Methodologies

Vincenzo Piuri, Sandeep Raj, Angelo Genovese, Rajshree Srivastava
Intelligent Data Analysis for Biomedical Applications

Intelligent Data Analysis for Biomedical Applications

D. Jude Hemanth, Deepak Gupta, Valentina Emilia Balas

Publisher Resources

ISBN: 9781800562967Supplemental Content