Red Hat OpenShift / OpenShift Commons Machine Learning SIG Meeting

OpenDataHub Fraud Detection
ML SIG
OpenShift Commons
July 12 2019

Open Data Hub project is a reference architecture for an AI and Machine Learning as a service platform for OpenShift built using open source tools.

OpenShift Commons Briefing
ML SIG March 2019 Full
MLFlow Intro and Operator
Mani Parkhe (Databricks)
Zak Hassan (Red Hat)
Diane Mueller (Red Hat)

OpenShift Commons
ML SIG Meeting
March 1 2019 Full Meeting Recording
MLFlow Introduction and MLFlow Operator demo
Databricks Mani Parkhe
Red Hat Zak Hassan and Diane Mueller

Jirika Kresmer (Red Hat)
GCP Spark Operator
Radanalytic.io Spark Operator
JVM Operators
Kubernetes and Operators
Operator Framework

Spark Operators
Using Ceph for ML workloads on OpenShift

Laval University Case Study
Guest Speaker: Guillaume Moutier (Laval University)
Data Science Services (Valeria)

Jeremy Wei and Brian Huang of Jeremy Wei (Prophetstor) – Demonstration of predicting computing resources usage for both nodes and containers, as well as predicting hardware issues.

"Data Hub" is a collection of open source and cloud components deployed as a "machine learning-as-a-service" platform to solve internal business problems at Red Hat that enables teams to build, deploy, and execute analytic, machine learning and AI models.

Repeatable human tasks are being replaced by automation, creating significant opportunity and risk for Red Hat. AI can be applied to our core business and direct customer services. To do so, data must be seamlessly unified from a broad range of sources and made accessible to analytic models.

This presentation is about how Red Hat runs AI and machine learning workloads on OpenShift.