Join our new monthly virtual meetup for the IBM Data Science Community, covering the latest in data science and AI. This event is co-hosted by our Data, Cloud and AI in San Francisco
meetup group (feel free to RSVP here, or over there, or both). December and January events to be announced shortly. See you there!
- Welcome + announcements (5')
- Talk + Q&A (35')
- Hang out & networking
Deep Learning models are getting more and more popular but constraints on explainability, adversarial robustness and fairness are often major concerns for production deployment. Although the open source ecosystem is abundant on addressing those concerns, fully integrated, end-to-end systems are lacking in open source. CLAIMED is an entirely open source, reusable component framework, visual editor and execution engine for production-grade machine learning on top of Kubernetes. It uses Kubeflow Pipelines, the AI Explainability360 toolkit, the AI Fairness360 toolkit, and the Adversarial Robustness Toolkit on top of ElyraAI, Kubeflow, Kubernetes and JupyterLab. Using the Elyra pipeline editor, AI pipelines can be developed visually with a set of Jupyter notebooks.
Join this virtual meetup to learn about CLAIMED and find out how you can get involved.
Romeo Kienzler, Data Scientist at the IBM Center for Open Source Data and AI Technologies (CODAIT).#datascience#Elyra#Jupyter#opensource#explainability#fairness#AIX#AIF#Kubernetes#kubeflow