You're reading from Machine Learning with the Elastic Stack - Second Edition

Product typeBook

Published inMay 2021

Reading LevelBeginner

PublisherPackt

ISBN-139781801070034

Edition2nd Edition

Languages

Python

Tools

Elasticsearch

Concepts

Machine Learning

Authors (3):

Rich Collier

Camilla Montonen

Bahaaldine Azarmi

View More author details

Managing Elastic ML via the API

As with just about everything in the Elastic Stack, ML can also be completely automated via API calls—including job configuration, execution, and result gathering. Actually, all interactions you have in the Kibana UI leverage the ML API behind the scenes. You could, for example, completely write your own UI if there were specific workflows or visualizations that you wanted.

Note

For more in-depth information about the anomaly detection APIs, please refer to elastic.co/guide/en/machine-learning/current/ml-api-quickref.html. The data frame analytics part of Elastic ML has a completely separate API, which will be discussed in Chapters 9 to 13.

We won't go into each API call, but we would like to highlight some parts that are worth a detour.

The obvious first API to mention is the job creation API, which allows the creation of the ML job configuration. For example, if you wanted to recreate the population analysis job shown in Figure...

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Machine Learning with the Elastic Stack - Second Edition

Published in: May 2021Publisher: PacktISBN-13: 9781801070034

Authors (3)

Rich Collier

Rich Collier is a solutions architect at Elastic. Joining the Elastic team from the Prelert acquisition, Rich has over 20 years' experience as a solutions architect and pre-sales systems engineer for software, hardware, and service-based solutions. Rich's technical specialties include big data analytics, machine learning, anomaly detection, threat detection, security operations, application performance management, web applications, and contact center technologies. Rich is based in Boston, Massachusetts.
Read more about Rich Collier

Camilla Montonen

Camilla Montonen is a Senior Machine Learning Engineer at Elastic.
Read more about Camilla Montonen

Bahaaldine Azarmi

Bahaaldine Azarmi, Global VP Customer Engineering at Elastic, guides companies as they leverage data architecture, distributed systems, machine learning, and generative AI. He leads the customer engineering team, focusing on cloud consumption, and is passionate about sharing knowledge to build and inspire a community skilled in AI.
Read more about Bahaaldine Azarmi

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Managing Elastic ML via the API

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