This notebook demonstrates how to use the Microsoft Azure Anomaly Finder Service.
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Updated
Jun 3, 2019 - HTML
This notebook demonstrates how to use the Microsoft Azure Anomaly Finder Service.
This repository is part of an article about how to forecast and detect anomalies on time-series data. The main objective is to train a RNN regressor on the Bitcoin dataset to predict future values on then detect anomalies in the whole data window - that last step achieved by implementing a RNN Autoencoder. You'll see some other models in the not…
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