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Operationalizing Machine Learning with Java Microservices and Stream Processing

Webinar

November 19, 2019 @ 8:00am PST / 11:00am EST / 4:00pm GMT
60 minutes

Are you ready to take your algorithms to the next steps and get them working on real-world data in real-time? We will walk through an architecture for taking a machine learning model into deployment for inference within an open source platform designed for extremely high throughput and low latency.

We’ll demonstrate a working example of a machine learning model being used on streaming data within the Hazelcast In-Memory Computing Platform, a powerful technology for distributed in-memory processing. We will also touch on important considerations to ensure maximum flexibility for deployments that need the flexibility to run either on-premises or in the cloud.

Can’t attend the live times? You should still register! We’ll be sending out the recording after the webinar to all registrants.

Presented By:

Scott McMahon
Senior Solutions Architect
Hazelcast

Scott McMahon is a Senior Solutions Architect at Hazelcast® with over 20 years of software development and enterprises consulting experience. Before specializing in Hazelcast In Memory Data Grid technology he built big data analytics platforms and business process management systems for many of the worlds leading corporations. He currently lives in Portland, Oregon, and when not working on computer systems, he enjoys getting outdoors and having fun with his family.

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