Dean Wampler helps you develop a conceptual understanding of the challenges faced by your teams as they develop and deploy machine learning and artificial intelligence services integrated with fast data (streaming) pipelines. While combining these technologies is challenging, the benefits include timely delivery of innovative services to your customers.
Dean begins by briefly discuss machine learning use cases that are best delivered as streaming data applications. He then explores the main challenges faced when deploying these technologies together and outline solutions to these challenges, including criteria to use when evaluating choices. Along the way, he explains the tools your teams are already talking about and the role they play.
Dean Wampler is the vice president of fast data engineering at Lightbend, where he leads the Lightbend Fast Data Platform project, a distribution of scalable, distributed stream processing tools including Spark, Flink, Kafka, and Akka, with machine learning and management tools. Dean’s the author of Programming Scala and Functional Programming for Java Developers and the coauthor of Programming Hive, all from O’Reilly. He’s a contributor to several open source projects. A frequent Strata speaker, he’s also the co-organizer of several conferences around the world and several user groups in Chicago.
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