With the mass amounts of data that are being ingested daily it is nearly impossible by traditional means to understand what is hidden in your data. How do you separate the ordinary from the un-ordinary in a timely fashion?
Unsupervised machine learning on time series data enables real-time discovery of those interesting and possibly costly data anomalies. During this presentation, Matteo Rebeschini, Solutions Architect at Elastic will describe, build and run several types of machine learning jobs in Elasticsearch that can detect and alert on these anomalies and outliers in real time.
Food and beverages will be provided.
*** Event Agenda ***
5:30PM - 6:00PM Networking
6:00PM - 7:00PM Presentation
7:30PM - 8:30PM Q&A and Networking
*** About the Speaker ***
Matteo Rebeschini is a Solutions Architect/Security Specialist at Elastic, where he works with customers on architecting real-time security analytics solutions using the Elastic Stack. Matteo has 18+ years of experience in the cybersecurity industry covering various roles, from software engineering to technical product management and more recently consulting and solutions architecture.