ML Model insights and Observability at the Edge - Wallaroo.AI

Learn how to get instant data insights and drift detection alerts from pipelines deployed at edge locations without any operational overhead. See how you to create aggregated drift detection assays on inputs and outputs for the pipelines deployed in an ML operations center & all the edge deployments Why should I attend? You will leave this session with a comprehensive understanding about how to observe ML models deployed at the edge for data drift and take corrective action for under performing models. About our speaker: John Hansarick is the Senior Technical Writer for Wallaroo.AI. His 29 year in the tech industry includes software developer, project manager, janitor, and network administrator. Working with companies from a variety of industries, he focuses on helping organizations understand how to use IT and machine learning models to solve problems. He is known to his coworkers for furthering the company's knowledge base, problem solving skills, and culinary creations. Resources: Try this Computer Vision model and other common AI use cases using the Wallaroo.AI Azure Inference Server Freemium Offer on Azure Marketplace (https://portal.azure.com) and also try the Free Wallaroo.AI Community Edition (https://portal.wallaroo.community/) Check out the Wallaroo.AI series! https://aka.ms/Wallaroo.AI Azure Marketplace Freemium Plans - https://aka.ms/Wallaroo.AI-Free Thanks! [eventID:21379]