Table of Contents
Preface
Section 1 – Getting Started with Machine Learning with Elastic Stack
Chapter 1: Machine Learning for IT
Overcoming the historical challenges in IT
Dealing with the plethora of data
The advent of automated anomaly detection
Unsupervised versus supervised ML
Using unsupervised ML for anomaly detection
Defining unusual
Learning what's normal
Probability models
Learning the models
De-trending
Scoring of unusualness
The element of time
Applying supervised ML to data frame analytics
The process of supervised learning
Summary
Chapter 2: Enabling and Operationalization
Technical requirements
Enabling Elastic ML features
Enabling ML on a self-managed cluster
Enabling ML in the cloud – Elasticsearch Service
Understanding operationalization ...
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