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MLOps Tutorial Series
How to create an automatic model training & testing setup using GitHub Actions and Continuous Machine Learning (CML).
ci-cd ml-ops production github-actions
You Trained a Machine Learning Model, Now What?
Three often overlooked parts of this process occur after the model is actually built: model evaluation, deployment, and monitoring.
production deployment monitoring video
Battle-Tested Techniques for Scoping Machine Learning Projects
One of the challenges of managing an ML project is project scoping. Even small changes in data or architecture can create huge differences in model ...
project-management production systems-design code
Deploying your ML Model with TorchServe
In this talk, Brad Heintz walks through how to use TorchServe to deploy trained models at scale without writing custom code.
serving production torchserve tutorial
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