Beginning Anomaly Detection Using

CHAPTER 6

Long Short-Term  

Memory Models

In this chapter, you will learn about recurrent neural networks and long short-term 

memory models. You will also learn how LSTMs work and how they can be used to 

detect anomalies and how you can implement anomaly detection using LSTM. You 

will work through several datasets depicting time series of different types of data such 

as CPU utilization, taxi demand, etc. to illustrate how to detect anomalies. This chapter 

introduces you to many concepts using LSTM so as to enable you to explore further 

using the Jupyter notebooks provided as part of the book material.

In a nutshell, the following topics will be covered throughout this chapter:

•  Sequences and time series analysis

•  What is a RNN?

•  What is an LSTM?

•  LSTM applications