- Tue, Nov 14, 2017 08:30 PM
16D Avenida de Burgos
Latitude: 40.4755, Longitude: -3.67526
Applying my Netflix experience to a real-world problem in the ML and AI world, I will demonstrate a full-featured, open-source, end-to-end TensorFlow Model Training and Deployment System using the latest advancements from Kubernetes, Istio, and TensorFlow. In addition to training and hyper-parameter tuning, our model deployment pipeline will include continuous canary deployments of our TensorFlow Models into a live, hybrid-cloud production environment. This is the holy grail of data science - rapid and safe experiments of ML / AI models directly in production. Following the Successful Netflix Culture that I lived and breathed ((https://www.slideshare.net/reed2001/culture-1798664/2-Netflix_CultureFreedom_Responsibility2), I give Data Scientists the Freedom and Responsibility to extend their ML / AI pipelines and experiments safely into production. Offline, batch training and validation is for the slow and weak. Online, real-time training and validation on live production data is for the fast and strong. Learn to be fast and strong by attending this meetup. Bio: Chris Fregly is Founder and Research Engineer at PipelineAI, a Streaming Machine Learning and Artificial Intelligence Startup based in San Francisco. He is also an Apache Spark Contributor, a Netflix Open Source Committer, founder of the Global Advanced Spark and TensorFlow Meetup, author of the O’Reilly Training and Video Series titled, "High Performance TensorFlow in Production." Previously, Chris was a Distributed Systems Engineer at Netflix, a Data Solutions Engineer at Databricks, and a Founding Member and Principal Engineer at the IBM Spark Technology Center in San Francisco.