This algorithm performs time series anomaly detection with a Long Short-Term Memory Network Autoencoder (LSTM-AE). It implements both training and inference from CSV data and supports both CPU and GPU instances. The training and inference Docker images were built by extending the PyTorch 2.1.0 Python 3.10 SageMaker containers. The algorithm can be used for both univariate and multivariate time series.