Applied Deep Learning with Keras

Chapter 9

Sequential Modeling with Recurrent Neural Networks

Learning Objectives

By the end of this chapter, you will be able to:

• Explain sequential memory and sequential modeling
• Explain Recurrent Neural Networks (RNNs)
• Describe the vanishing gradient problem
• Implement Long Short-Term Memory (LSTM) architectures
• Apply RNNs on a stock market dataset

In this chapter, we will learn about sequential modeling with RNNs using the stock price data of Apple and Microsoft. We will understand the vanishing gradient problem and, finally, we will implement the concept of LSTM.

Introduction

Neural networks are the building blocks of all deep learning models. In traditional neural networks, all the inputs and outputs are independent. However, there ...