
Elastic Stack 8.x Cookbook
By :

Now that you have trained some models using Elastic, we will look at how you can use them for prediction through a process called inference. It is a process of using trained ML models against incoming data in a continuous way. In the Elastic Stack, this process happens essentially through an inference processor in ingest pipelines or pipeline aggregation.
In this recipe, we’ll build upon the classification model we trained in the previous recipe, configure it into an ingest pipeline processor, and use it for prediction.
Make sure you have worked through the following recipes:
The snippets for this recipe can be found at https://github.com/PacktPublishing/Elastic-Stack-8.x-Cookbook/blob/main/Chapter8/snippets.md#using-trained-model-for...