Multivariate Anomaly Detection - Testing and Best Practices

To recap, in the previous lesson, we prepared and uploaded the dataset to Azure blob storage and generated the SAS URL. Then, we submitted a request for model training to detect the multi-variate anomalies in the dataset. After that, we have checked the status of the model.

Detecting anomalies using the trained model

Once the model is trained successfully, it’s ready to detect the anomalies in the dataset.