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Please note: This schedule is automatically displayed in Central European Summer Time (UTC +2). To see the schedule in your preferred timezone, please select from the drop-down menu to the right, above "Filter by Date." The schedule is subject to change and session seating is available on a first-come, first-served basis.
MLOps is used in various organizations, that operate on very sensitive datasets. Pharmaceutical and life science companies handling human DNA samples, healthcare institutions training models on patient data, or highly regulated environments like telecom and financial companies. Many users are afraid that cloud-native would expose them more to vulnerabilities, data leaks, or other security issues. In reality, it's just the opposite. With Kubernetes and its ecosystem - Kubeflow, strict confinement for K8s using AppArmor profiles, confidential computing in case you run your workloads on the public cloud and blockchain-based tokenization you can achieve very safe and compliant setup. On the talk you will see a case study of a LifeSciences company creating customized treatments based on DNA, utilizing above mentioned technologies to run complex hybrid/multi-cloud MLOps using Kubernetes and Kubeflow.
I'm a Principal AI/ML Engineer at Canonical - the publisher of Ubuntu.My specialties are:▪ Machine Learning and Data Engineering ▪ Solutions Architecture - Data Lakes / Lakehouse, MLOps pipelines, real-time streaming▪ Public Clouds: AWS, Azure and GCP▪ Kubernetes at scale... Read More →
I am a Product Manager at Canonical, leading the MLOps area. With a background in Data Science in various industries, such as retail or telecommunications, I used AI techniques to enable enterprises to benefit from their initiatives and make data-driven decisions. I am looking to... Read More →
