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

Section 3 – Data Frame Analysis

This section covers the basics of data frame analysis, what it is useful for, and how you will be able to implement it. It covers various types of analysis and how they differ from each other. At the end, the section covers some useful tidbits that can be used to get the most out of Elastic ML.

This section covers the following topics:

Chapter 9, Introducing Data Frame Analysis
Chapter 10, Outlier Detection
Chapter 11, Classification Analysis
Chapter 12, Regression
Chapter 13, Inference
Appendix: Anomaly Detection Tips

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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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