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Speaker "Chris Fregly" Details Back

 

Topic

Continuous Spark ML and Tensorflow AI Model Training and Deployment Across Hybrid Cloud Environments
 

Abstract

In this completely demo-based talk, Chris Fregly from PipelineAI will demo the latest 100% open source research in high-scale, fault-tolerant Spark ML and Tensorflow AI Model Training and Serving across a Hybrid AWS, Google, and Azure deployment environment.
 
All demos will use 100% open source tools including Jupyter Notebook, Docker, Kubernetes, Airflow, Spark, Tensorflow, and NetflixOSS Microservices.  
 
Chris will focus on continuous ML/AI model deployment, auto-scaling within a cloud environment, and "auto-shifting" between cloud environments for eXtreme High Availability (XHA) and cost-savings.
 
Everything will originate from a single Jupyter Notebook.  All code is 100% open source and available here:  https://github.com/fluxcapacitor/pipeline.  All Docker images are available here:  https://hub.docker.com/u/fluxcapacitor/
 
This talk will be one of a kind as there nobody else in the world is doing this type of advanced ML/AI deployment strategy.  And we'll do it live on stage!  
 

Profile

Chris Fregly is a Developer Advocate for AI and Machine Learning at Amazon Web Services (AWS) based in San Francisco, California. He is co-author of the O'Reilly Book, "Data Science on AWS."
 
Chris is also the Founder of many global meetups focused on Apache Spark, TensorFlow, and KubeFlow. He regularly speaks at AI and Machine Learning conferences across the world including O’Reilly AI & Strata, Open Data Science Conference (ODSC), and GPU Technology Conference (GTC).
 
Previously, Chris was Founder at PipelineAI where he worked with many AI-first startups and enterprises to continuously deploy ML/AI Pipelines using Apache Spark ML, Kubernetes, TensorFlow, Kubeflow, Amazon EKS, and Amazon SageMaker.