Kubernetes: Simplifying Machine Learning Workflows
Kubernetes: Simplifying Machine Learning Workflows

Abstract: 

You know Kubernetes is a great platform for the applications you’re running today. Most of the applications you’ll be excited about tomorrow are intelligent applications, which collect data and rely on machine learning to support essential functionality. These capabilities often seem like magic to users, but building applications and services that leverage artificial intelligence is more accessible than you might think. This workshop will show how Kubernetes, the most popular open source container orchestration platform, can increase collaboration and decrease time to value for machine learning workflows. Attendees will be able to create workflows with ease, deploy models as micro-services and monitor performance to understand when retraining is needed. We’ll focus on the open source infrastructure, tools and processes that will help you to get meaningful results from application intelligence and show why Kubernetes is the best place for data science workloads. You’ll leave having solved a real business problem interactively with powerful machine learning techniques and Kubernetes.

Bio: 

Sophie is a software engineer at Red Hat, where she works in an emerging technology group. She has a background in Mathematics and has recently completed a PhD in Bayesian statistics, in which she developed algorithms to estimate intractable quantities quickly and accurately. Since joining Red Hat in 2017, Sophie has focused on applying her data science and statistics skills to solving business problems and informing next-generation infrastructure for intelligent application development.

Platform Prerequisite 

To facilitate the hands-on sessions, we are delighted to announce that DataRobot, our diamond partner, is providing hands-on session attendees with free access to their AI platform. 

Many of our workshops  and tutorials will utilize the AI Platform for instruction and collaboration. It automates the end-to-end process for building, deploying, and maintaining AI at scale and also provides feature engineering, auto model evaluation, and advanced machine learning techniques. It comes preloaded with models and datasets so you can get started prior to the event.  Please note: YOU MUST BE REGISTERED TO GET FREE ACCESS to the AI Platform