Summary

In this chapter, we have looked at the various options available for using supervised models trained in Elasticsearch and external libraries such as scikit-learn. We have learned about the Trained Models API, which is useful when managing and examining trained supervised learning models in an Elasticsearch cluster and how to make use of these models to make predictions on previously unseen examples with the help of inference processors and ingest pipelines. In the appendix following this chapter, we will provide some tips and tricks that make it easier to work with the Elastic Machine Learning stack.