Once the models are published, you can use them to enrich the data loaded from any source by adding the models to the pipeline workflow.
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This takes you to the following screen which shows you all steps that can be added to an existing workflow. Under the section Classify all published models are shown. Here, you can choose the model you would like to use to enrich your data and add it to the pipeline via click and drop.
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Once the model has been added to the pipeline and was saved, it will appear with all the other steps and you can now use this workflow to load new and existing data sources and enrich it with the output from your machine learning model.
If you have published multiple models in the AIS, we also allow you to add multiple models in your pipeline as different steps. Each of these models can serve a different purpose in enriching your data and can augment the insights for the end-users using Squirro’s dashboards.
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This page can now be found at ML Enrichments for Pipeline Workflows on the Squirro Docs site.