The Easiest Way to Track Data Science Experiments with MLRun
Towards Data Science, Dec 28, 2019
MLRun is Iguazio's open source MLOps orchestration framework. MLRun enables you to run the same code either locally on your PC for a test or on a large scale Kubernetes cluster with minimal changes. Track all experiments with their parameters, inputs, outputs and labels.
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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.
