3-part webinar series: May 18, June 22, and July 1, 2021
Join us to discover why Red HatⓇ OpenShiftⓇ is the perfect platform for running your artificial intelligence/machine learning (AI/ML) workloads on-premise, cloud, or at the edge. Find out how Red Hat Consulting is helping customers operationalize their ML models through machine learning operations (MLOps) practices and see how it all runs on OpenShift. Whether you are deploying ML models into production, looking for a data science research platform, or just starting to explore AI/ML, this three-part webinar series is for you.
Webinar 1: Why choose Red Hat for AI/ML?
Find out how Red Hat supports customers running their AI/ML workflows on Red Hat OpenShift. Join Anne Dalton (Data Science and Edge Specialist), Sophie Watson (Principal Data Scientist), and John Hurlocker (Senior Architect, Red Hat Consulting) as they talk through the value of open source in developing and implementing data science and edge capabilities.
In this webinar, we’ll cover:
- Different AI/ML use cases and the challenges customers are facing when trying to bring these capabilities to the edge, and how Red Hat Consulting is helping customers overcome those challenges.
- Our engineering roadmap to show our commitment to these capabilities as we continue to enhance and expand our offerings in this space.
Live-event time: Tuesday, May 18, 2021 | 2 p.m. ET
Webinar 2: Experience hybrid cloud AI/ML at scale
Data Science practices face challenges of scale, reproducibility, on-premise and cloud data silos, and inconsistent deployments across environments. Red Hat has played a key role in solving these issues for agile software development, especially with DevSecOps principles and practice. Now, Red Hat is applying that experience and perspective to principled Machine Learning Model Operationalization Management practices at scale. Please join us as we use Red Hat OpenShift Container Platform and ML for the detection of pneumonia from chest x-rays. This cloud-agnostic solution uses popular ML tools for running large and distributed workloads across disparate multicloud data sets. Compute resources are spun up on-demand, and scale to 0 as compute jobs reach completion, while edge-deployed ML models that show low degrees of certainty are retrained in centralized data hubs and continuously deployed back to the healthcare environment. At scale, this data pipeline reduces compute latency, and facilitates continuous improvement and deployment for time-sensitive imaging and diagnostics.
Red Hat has a proven and global track record of helping organizations operationalize AI/ML solutions in multicloud and hybrid cloud environments using open source tools for data harmonization, distributed AI and ML workflows, and the emerging practice of MLOps.
Live-event time: Tuesday, June 22, 2021 | 2 p.m. ET
Webinar 3: Intelligent applications on OpenShift
Discover how to create and manage intelligent applications that learn and make decisions on Red Hat OpenShift. We will showcase the latest advancements in MLOps, serverless event driven architecture, and business automation with a demonstration of all of three in action.
This webinar highlights how to weave the following technologies into a seamless, high-performance platform for delivering data products:
- Red Hat OpenShift Container Storage
- A computer vision machine learning model
- Red Hat’s Kogito serverless technology for business automation
- Seldon for model serving and monitoring
Live-event time: Thursday, July 1, 2021 | 2 p.m. ET
On-demand event: Available for one year after live-event date.