A Convolutional Autoencoder for Time-Series Data Anomaly Detection

Why do k-means and GMM algorithms fail on unprocessed time-series data? Here’s how you can create your own custom anomaly detection learning block, leveraging the benefits of a convolutional autoencoder architecture for time-series data anomaly detection.