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Deploy Spark ML and Tensorflow AI Models from Notebooks to Microservices - Nov 16 2016 - Madrid

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In this completely 100% Open Source demo-based talk, Chris Fregly from PipelineIO will be addressing an area of machine learning and artificial intelligence that is often overlooked: the real-time, end-user-facing "serving” layer in a hybrid-cloud and on-premise deployment environment using Jupyter, NetflixOSS, Docker, and Kubernetes.

Serving models to end-users in real-time in a highly-scalable, fault-tolerant manner requires not only an understanding of machine learning fundamentals, but also an understanding of distributed systems and scalable microservices.

Chris will combine his work experience from both Databricks and Netflix to present a 100% open source, real-world, hybrid-cloud, on-premise, and NetflixOSS-based production-ready environment to serve your notebook-based Spark ML and TensorFlow AI models with highly-scalable and highly-available robustness.


Speaker Bio

Chris Fregly is a Research Scientist at PipelineIO - a Streaming Analytics and Machine Learning Startup in San Francisco.

Chris 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, and Creator of the upcoming O'Reilly video series, Scaling TensorFlow Distributed in Production.

Previously, Chris was an engineer at Databricks and Netflix - as well as a Founding Member of the IBM Spark Technology Center in San Francisco.

Published in: Software

Deploy Spark ML and Tensorflow AI Models from Notebooks to Microservices - Nov 16 2016 - Madrid

  1. 1. INNOVATION TECHNOLOGY MEETUP @ BEEVA Deploy Spark andTensorflow Models: From Notebook Dev to Microservice Prod Madrid - November 16, 2016 ThankYou, BEEVA! http://pipeline.io http://beeva.com
  2. 2. WHO AM I? Chris Fregly -------- Research Scientist @ PipelineIO (Formerly Netflix and Databricks) -------- http://pipeline.io
  3. 3. WHO ARE YOU? -- LocalTechies --
  4. 4. FUN WORKSHOP ON SATURDAY! (HERE IN MADRID) http://pipeline.io#upcoming-workshops
  5. 5. SOURCE CODE AND DOCKER IMAGES • Github Repo: 900 Stars, 300 Forks • DockerHub Repo: 6,200 Pulls
  6. 6. WHAT IS PIPELINE.IO? ExtendingYour ML Pipelines into Production 100% Open Source! http://pipeline.io
  7. 7. BRAINSTORMING AND VALIDATING • Major Gaming Company • Large Ride Sharing Service • Popular Q & A Site • Online Clothing Retailer • DominantVideo Streaming
  8. 8. PIPELINE.IO FOCUS • Model Deploying andTesting • Model Scaling and Serving • Online ModelTraining • Dynamic Model Optimizing
  9. 9. MODEL DEPLOYING AND TESTING Continuously Test and Deploy Models in Production!
  10. 10. MODEL SCALING AND SERVING
  11. 11. ONLINE MODEL TRAINING • Continuous, Incremental, and Partial Training • Kafka + Spark Streaming + Spark ML • Real-time, Dynamic Recommendations
  12. 12. DYNAMIC MODEL OPTIMIZING Generate Optimized Code from Spark ML!
  13. 13. BECOME A CONTRIBUTOR!
  14. 14. PIPELINE.IO PLAN FOR 2017 • Performance • Code Generation: CPU and GPU • Continued Global Expansion
  15. 15. MORE WORKSHOPS IN 2017 http://pipeline.io#upcoming-workshops
  16. 16. WE’RE HIRING!! • Kafka, Spark ML, and TensorFlow Contributors • Systems Engineers • GPU/CUDA Engineers • C++, Java, Scala, Python WE ONLY HIRE NICE PEOPLE!!
  17. 17. DEMO! Circuit Breakers and Request Batching
  18. 18. DEMO! Deploy Spark ML DecisionTree to Production Deploy to Cloud or On-Premise!
  19. 19. DEMO! Dynamic Code Generation of DecisionTree
  20. 20. DEMO: TENSORFLOW SERVING
  21. 21. THANK YOU!! http://pipeline.io http://beeva.com

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