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Consume MLRun, the scalable open source pipeline orchestration framework as a managed service in the Iguazio Data Science Platform. Leverage automation, scale and high performance to boost workflow management, experiment tracking and reproducability.
Run multiple experiments in parallel, each using a different combination of algorithm functions and parameter sets (hyper-parameters) to automatically select the best result.
Describe and track code, metadata, inputs and outputs of machine learning related tasks (executions) and re-use results with a generic and easy-to-use mechanism.
Maintain the same set of features in the training and inferencing (real-time) stages with MLRun's unified feature store.
Natively integrate with Kubeflow Pipelines to compose, deploy and manage end-to-end machine learning workflows with UI and a set of services.
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Director of DXP Innovation
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Lead Data Scientist and Growth Hacker
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