This article introduces training machine learning models in Domino. See the links below to learn about Domino’s benefits and model development concepts.
Domino is a flexible platform that’s designed to work with your favorite tools:
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Develop and train models with open-source libraries and your favorite IDEs.
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Implement MLflow to track and monitor experiments in R and Python.
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Scale distributed workloads with Dask, Ray, MPI, and Spark.
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Tune hyperparameters at scale with Ray Tune and other open source libraries.
Domino helps you manage experiments and models across your organization:
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Track and monitor experiments to see logs, outputs, and more.
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Schedule jobs for recurring processes.
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Develop projects with Git version control.
After you understand how to train models in Domino, learn how to Deploy Models and Apps.