About Session
Converging the data science world and the actual production world to deliver machine learning execution for high value insights is challenging enough, but we also want it to work in real time. The road from data capture, model development and deployment is often disjoint and therefore filled with barriers and delays – starting with having significant data for training models.
Join this high energy morning kickoff to learn the pitfalls to avoid, the means to create a converged process and environment, and tips from the experts for operationalizing machine learning in event driven solution development and delivery.
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SPEAKERS
Steven Astorino
IBM, VP of Development, Hybrid Cloud, z Analytics and Canada Lab Director
- Software Development Executive with proven transformational leadership
- Excellent Client Relationship management with enterprise clients
- Expertise in leading large enterprise development teams
- Extensive experience with software development methodologies including Waterfall and Agile
- Experienced change agent with proven track record to drive improvements and efficiency
- Experienced software architect with solid understanding of applications and system development projects
Dean Wampler
Lightbend, VP of Fast Data Engineering
Dean Wampler, Ph.D., is the VP of Fast Data Engineering at Lightbend. He leads the development of Lightbend Fast Data Platform, a distribution of scalable, distributed stream processing tools including Spark, Flink, Kafka, and Akka, with machine learning and management tools. Dean is the author of several books, a frequent conference speaker and organizer, and he helps run several Meetups in Chicago.
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