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Practical Machine Learning: A New Look at Anomaly Detection
book

Practical Machine Learning: A New Look at Anomaly Detection

by Ted Dunning, Ellen Friedman
August 2014
Intermediate to advanced
66 pages
1h 25m
English
O'Reilly Media, Inc.
Content preview from Practical Machine Learning: A New Look at Anomaly Detection

Appendix A. Additional Resources

GitHub

For the code mentioned in this publication:

Code for t-digest
https://github.com/tdunning/t-digest
EKG anomaly detection example
https://github.com/tdunning/anomaly-detection
Simple event sequence model example
https://github.com/tdunning/sequencemodel

Apache Mahout Open Source Project

The clustering algorithm mentioned in this publication is from Apache Mahout.

For more information on the Apache Mahout project for scalable machine learning, please visit the Mahout website. This project welcomes participation. Please feel free to subscribe to the user or developer mailing lists, check the mail archives to see discussions, and follow the community on Twitter at @ApacheMahout.

Additional Publications

To learn how to build a simple but powerful recommendation system, please download Practical Machine Learning: Innovations in Recommendation, also written by Ted Dunning and Ellen Friedman.

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Publisher Resources

ISBN: 9781491914151Errata