Continuous Spark ML & Tensorflow AI Training & Deployment Across Hybrid Cloud

NOTE SPECIAL DAY: TUESDAY  

(Seating is limited to 150 people, so please un-RSVP if you change your mind) 

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

Chris Fregly, Research Scientist, PipelineAI

Agenda 

6:30 Doors Open, Food & Networking  
7:00 Presentation  
*** Please arrive by 7 PM due to Security ***

Event Details

In this completely demo-based talk, Chris Fregly from PipelineIO 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/

Speaker Bio

Chris Fregly is a Research Scientist at PipelineAI – a Machine Learning and Artificial Intelligence Startup in San Francisco. Chris is an Apache Spark Contributor, Netflix Open Source Committer, Founder of “Advanced Spark and TensorFlow Meetup”, and Author of the upcoming O’Reilly Video Series and Online Training “High Performance Tensorflow in Production: Hands-on Experience Training and Serving Tensorflow AI Models with GPUs Across Hybrid Cloud and On-Premise Deployment Environments” Previously, Chris was a Distributed Systems Engineer at Netflix, Data Solutions Engineer at Databricks, and a Founding Member of the IBM Spark Technology Center in San Francisco. 

https://www.linkedin.com/in/cfregly/

Event page provided by ACM