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Akshaya Annavajhala
2020-08-10 16:17:36 -07:00
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how-to-use-azureml/track-and-monitor-experiments/README.md
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[MLflow](https://mlflow.org/) is an open-source platform for tracking machine learning experiments and managing models. You can use MLflow logging APIs with Azure Machine Learning service: the metrics and artifacts are logged to your Azure ML Workspace.
Try out the sample notebooks:
1. [Use MLflow with Azure Machine Learning for Local Training Run](./train-local/train-local.ipynb)
1. [Use MLflow with Azure Machine Learning for Remote Training Run](./train-remote/train-remote.ipynb)
1. [Use MLflow with Azure Machine Learning for Local Training Run](./using-mlflow/train-local/train-local.ipynb)
1. [Use MLflow with Azure Machine Learning for Remote Training Run](./using-mlflow/train-remote/train-remote.ipynb)
![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/MachineLearningNotebooks/how-to-use-azureml/track-and-monitor-experiments/README.png)