Chapter 13: Inference

In this chapter, we will take an in-depth look at all of the fascinating things you can do with trained supervised models in the Elastic Stack. First, we will see how to use the Trained Models API to view information about the models available in our cluster, to see details about individual models, and to export models so that they can be ported to other Elasticsearch clusters. We will also take a brief look at how to use eland to import external models, such as those trained by third-party machine learning libraries, into Elasticsearch.

In the second part of this chapter, we will go in-depth into how to use trained supervised models with inference in a variety of contexts to enrich data. To do this, we will learn about inference processors and ingest pipelines and how these can be combined with continuous transforms, reindexing, and at ingest time when using various beats or otherwise ingesting data into Elasticsearch.

In this chapter, we will cover the...