Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
Jonathan Merriman

Jonathan Merriman
Senior Software Engineer, Verint Intelligent Self Service

Jon Merriman is a senior software engineer and researcher at Verint Intelligent Self-Service, where he works on core natural language understanding capabilities for dialogue systems. His primary focus is on algorithms and machine learning theory for text and speech analysis.

Sessions

1:50pm–2:30pm Thursday, March 28, 2019
How to determine the optimal anomaly detection method for your application
Data Science, Machine Learning & AI
 Location: 2011
Secondary topics:  Temporal data and time-series analytics
Jonathan Merriman (Verint Intelligent Self Service), Cynthia Freeman (Verint Intelligent Self-Service)
Average rating: ***..
(3.89, 9 ratings)
Anomaly detection has many applications, such as tracking business KPIs or fraud spotting in credit card transactions. Unfortunately, there's no one best way to detect anomalies across a variety of domains. Jonathan Merriman and Cynthia Freeman introduce a framework to determine the best anomaly detection method for the application based on time series characteristics. Read more.