Exploring the world of model serving in machine learning, discussing serverless concepts, API endpoints, streaming and batch data, with a sprinkle of coffee vs tea banter. They touch on real-time prediction scenarios, optimizing model serving using Kubeflow, and challenges of deploying models in production. Delve into the practical applications of Kubeflow, model training with the Iris dataset, building custom model services, and planning in-depth MLOps discussions with audience engagement.
