YouTube Video: https://www.youtube.com/watch?v=RnnweVC7wFc 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.

1. ADVANCED SPARK
AND TENSORFLOW MEETUP
Deploy Spark andTensorflow Models:
From Notebook Dev to Microservice Prod
London - November 15, 2016
ThankYou, PipelineIO,Rise, Barclays!
http://pipeline.io

2. MEETUP AGENDA
• Meetup Updates, Metrics, and Announcements
• Spark Updates
• Tensorflow Updates
• Deploying and Scaling ML Models from
Notebook to Production with PipelineIO
(Chris Fregly, PipelineIO)

3. WHO AM I?
Chris Fregly
--------
Research Scientist @ PipelineIO
(Formerly Netflix and Databricks)
--------
http://pipeline.io

4. WHO ARE YOU?
--Techies of London --

5. FUN WORKSHOP LAST MONTH
(HERE IN LONDON)

6. MEETUP METRICS
• 10,000+ Members Globally in 1Year!
• 5,000 Members in San Francisco (Home)
• Github Repo: 900 Stars, 300 Forks
• DockerHub Repo: 6,200 Pulls

7. APACHE SPARK UPDATE

8. SPARK SUMMIT EU 2016 (BRUSSELS)
• https://spark-summit.org/eu-2016/schedule/
• Structured Streaming (2 talks)
• ML + Structured Streaming (1 talks)
• ML Model Deployment (2 talks)
• Spark Performance (4 talks)

9. TENSORFLOW UPDATE

10. TENSORFLOW WORKSHOP
• Great Workshop From Google Directly
• Finally, training involving more than MNIST!
• Slides
• http://bit.ly/tf-workshop-slides
• Workshop
• https://github.com/amygdala/tensorflow-workshop

11. WHAT IS PIPELINE.IO?
ExtendingYour ML Pipelines into Production
100% Open Source!
http://pipeline.io

12. BRAINSTORMING AND VALIDATING
• Major Gaming Company
• Large Ride Sharing Service
• Popular Q & A Site
• Online Clothing Retailer
• DominantVideo Streaming

13. PIPELINE.IO FOCUS
• Model Deploying andTesting
• Model Scaling and Serving
• Online ModelTraining
• Dynamic Model Optimizing

14. MODEL DEPLOYING AND TESTING
Continuously Test
and Deploy Models
in Production!

15. MODEL SCALING AND SERVING

16. ONLINE MODEL TRAINING
• Continuous, Incremental, and Partial Training
• Kafka + Spark Streaming + Spark ML
• Real-time, Dynamic Recommendations

17. DYNAMIC MODEL OPTIMIZING
Generate Optimized
Code from Spark ML!

18. BECOME A CONTRIBUTOR!

19. PIPELINE.IO PLAN FOR 2017
• Performance
• Code Generation: CPU and GPU
• Continued Global Expansion

20. MORE WORKSHOPS IN 2017

21. WE’RE HIRING!!
• Kafka, Spark ML, and TensorFlow Contributors
• Systems Engineers
• GPU/CUDA Engineers
• C++, Java, Scala, Python
WE ONLY HIRE
NICE PEOPLE!!

22. DEMO!
Circuit Breakers and Request Batching

23. DEMO!
Deploy Spark ML DecisionTree to Production
Deploy to Cloud
or On-Premise!

24. DEMO!
Dynamic Code Generation of DecisionTree

25. THANK YOU!!
http://pipeline.io