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Machine Learning with the Elastic Stack

You're reading from   Machine Learning with the Elastic Stack Expert techniques to integrate machine learning with distributed search and analytics

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788477543
Length 304 pages
Edition 1st Edition
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Authors (2):
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Bahaaldine Azarmi Bahaaldine Azarmi
Author Profile Icon Bahaaldine Azarmi
Bahaaldine Azarmi
Rich Collier Rich Collier
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Rich Collier
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Toc

Table of Contents (12) Chapters Close

Preface Machine Learning for IT FREE CHAPTER Installing the Elastic Stack with Machine Learning Event Change Detection IT Operational Analytics and Root Cause Analysis Security Analytics with Elastic Machine Learning Alerting on ML Analysis Using Elastic ML Data in Kibana Dashboards Using Elastic ML with Kibana Canvas Forecasting ML Tips and Tricks Other Books You May Enjoy

The orchestration

ML sequences all of these pieces together when an ML job is configured to run. A simplified version of this process is shown in the following diagram:

Simplified sequence of ML's procedures per bucket_span

In general, the preceding procedures are done once per bucket_span—however, additional optimizations are done to minimize I/O. Those details are beyond the scope of this book. The key takeaway, however, is that this orchestration enables ML to be online (that is, not offline/batch) and constantly learning on newly ingested data. This process is also automatically handled by ML so that the user doesn't have to worry about the complex logistics required to make it all happen.

You have been reading a chapter from
Machine Learning with the Elastic Stack
Published in: Jan 2019
Publisher: Packt
ISBN-13: 9781788477543
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