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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.
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Quick takeaways
- Serving models with Kubeflow involves using live endpoints for real-time predictions, ensuring accessibility to end users.
- Model serving through Kubeflow offers flexibility by abstracting serving frameworks and optimizing job creation for deployment.
Deep dives
Introduction to Coffee Break Sessions
Coffee Break Sessions is a new series where David and Demetrius explore deep dives into various topics, with David teaching Demetrius about different subjects. The goal is to engage with topics suggested by the audience or to have guests share their expertise.
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