Anomaly detection using an LSTM AE
In this recipe, we’ll build an AE to detect anomalies in time series. An AE is a type of neural network (NN) that tries to reconstruct the input data. The motivation to use this kind of model for anomaly detection is that the reconstruction process of anomalous data is more difficult than that of typical observations.
Getting ready
We’ll continue with the New York City taxi time series in this recipe. In terms of framework, we’ll show how to build an AE using PyTorch Lightning. This means that we’ll build a data module to handle the data preprocessing and another module for handling the training and inference of the NN.
How to do it…
This recipe is split into three parts. First, we build the data module based on PyTorch. Then, we create an AE module. Finally, we combine the two parts to build an anomaly detection system:
- Let’s start by building the data module. We create a class called...
