Hello wonderful big data developers and enthusiasts.
I’m very excited to announce our next event for this season, as we will have the unique opportunity of listening to Chris Fregly, a highly-experienced Data Engineer and Research Scientist from PipelineIO in San Francisco, who graciously agreed to come and present us some of the state-of-the-art Machine Learning techniques and processes utilizing Spark.
In this talk, Chris will discuss and demonstrate how to incrementally and continuously train a Spark ML-based recommendation model on real-time data from a Kafka source. In addition, we'll continuously deploy these new recommendation models into production using highly-available and highly-scalable Netflix Open Source tools.
Honesty speaking, I just tried to describe Chris' profile in a short paragraph, but then I realized I couldn't even fit his major achievements in one big paragraph, so I eventually asked him to "somehow" describe himself in a few lines. You should certainly take a look on Chris' LinkedIn profile (https://www.linkedin.com/in/cfregly) and I am sure you will immediately notice you cannot miss this lecture. Just imagine that Chris is the founder of the 4500+ Members Advanced Spark And Tensorflow Meetup (https://www.meetup.com/Advanced-Spark-and-TensorFlow-Meetup/) in San Francisco, CA.
Speaker's ProfileChris Fregly is currently a Research Scientist at PipelineIO - a Streaming Analytics and Machine Learning Startup in San Francisco.
He is an Apache Spark Contributor, Netflix Open Source Committer, Founder of the Global Advanced Spark and TensorFlow Meetup, and Author of the Upcoming Book, Advanced Spark.
Previously, Chris was a Streaming Data Engineer at Databricks and Netflix - as well as a Founding Member of the IBM Spark Technology Center in San Francisco.
