You're reading from Machine Learning with the Elastic Stack Gain valuable insights from your data with Elastic Stack's machine learning features

Product type Paperback

Published in May 2021

Publisher Packt

ISBN-13 9781801070034

Length 450 pages

Edition 2nd Edition

Languages

Python

Tools

Elasticsearch

Concepts

Machine Learning

Authors (3):

Camilla Montonen

Rich Collier

Bahaaldine Azarmi

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Table of Contents (19) Chapters

Preface

1. Section 1 – Getting Started with Machine Learning with Elastic Stack

2. Chapter 1: Machine Learning for IT FREE CHAPTER

3. Chapter 2: Enabling and Operationalization

4. Section 2 – Time Series Analysis – Anomaly Detection and Forecasting

5. Chapter 3: Anomaly Detection

6. Chapter 4: Forecasting

7. Chapter 5: Interpreting Results

8. Chapter 6: Alerting on ML Analysis

9. Chapter 7: AIOps and Root Cause Analysis

10. Chapter 8: Anomaly Detection in Other Elastic Stack Apps

11. Section 3 – Data Frame Analysis

12. Chapter 9: Introducing Data Frame Analytics

13. Chapter 10: Outlier Detection

14. Chapter 11: Classification Analysis

15. Chapter 12: Regression

16. Chapter 13: Inference

17. Other Books You May Enjoy

Appendix: Anomaly Detection Tips

Working with Python and Elasticsearch

In recent years, Python has become the dominant language for many data-intensive projects. Fueled by its easy-to-use machine learning and data analysis libraries, many data scientists and data engineers are now heavily relying on Python for most of their daily operations. Therefore, no discussions of machine learning in the Elastic Stack would be complete without exploring how a data analysis professional can work with the Elastic Stack in Python.

In this section, we will take a look at the three official Python Elasticsearch clients, understand the differences between them, and discuss when one might want to use one over the others. We will demonstrate how usage of Elastic Stack ML can be automated by using Elasticsearch clients. In addition, we will take a deeper look at Eland, the new data science native client that enables efficient in-memory data analysis backed by Elasticsearch. After exploring how Eland works, we will illustrate how...