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

Contrasting forecasting with prophesying

Past performance is not indicative of future results. This disclaimer is used by financial companies when they reference the performance of products such as mutual funds. But this disclaimer is a bit of an odd contradiction, because the past is all that we have to work with. If the companies that comprise the mutual fund have had consistently positive quarterly results for the last eight quarters straight, does that guarantee that they will also have a positive set of results for the next eight quarters and that their public valuation will continue to rise? Probability could be on the side of that being the case, but that might not be the whole story. And, before we get too wishful in thinking that Elastic ML’s ability to forecast is our key to making a fortune in the stock market, we should be realistic about one key caveat—there are always uncontrollable factors.

The reason financial companies use the preceding disclaimer...