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Machine Learning with the Elastic Stack - Second Edition

You're reading from  Machine Learning with the Elastic Stack - Second Edition

Product type Book
Published in May 2021
Publisher Packt
ISBN-13 9781801070034
Pages 450 pages
Edition 2nd Edition
Languages
Authors (3):
Rich Collier Rich Collier
Profile icon Rich Collier
Camilla Montonen Camilla Montonen
Profile icon Camilla Montonen
Bahaaldine Azarmi Bahaaldine Azarmi
Profile icon Bahaaldine Azarmi
View More author details

Table of Contents (19) Chapters

Preface 1. Section 1 – Getting Started with Machine Learning with Elastic Stack
2. Chapter 1: Machine Learning for IT 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...

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