Keras Implementation of time series anomaly detection using an Autoencoder ⌛
This repo contains the model and the notebook for this time series anomaly detection implementation of Keras.
Full credits to: Pavithra Vijay
Background Information
This notebook demonstrates how you can use a reconstruction convolutional autoencoder model to detect anomalies in timeseries data.
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# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("keras-io/time-series-anomaly-detection-autoencoder")