kedro-azureml
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Kedro plugin to support running workflows on Microsoft Azure ML Pipelines
The `pipeline_ml_factory` method in kedro-mlflow is a useful method to store artifacts (transformers, models) automatically (using kedro-mlflow hook). However, this method calls the method [extract_pipeline_artifacts](https://github.com/Galileo-Galilei/kedro-mlflow/blob/9df9c23b3ceb88fada34dc7bc939992b08c807bf/kedro_mlflow/mlflow/kedro_pipeline_model.py#L148) which requires the `_filepath` attribute...
It would be nice to support versioning of the underlying dataset in AzureMLPipelineDataSet when running the pipeline locally. We could dynamically disable the versioning then in the Azure ML runner....
For consistency it should be possible to override the resource group and workspace name when using the CLI, just like it is possible to override the subscription ID now. _Originally...
Right now, there is no support for kedro-mlflow as it handles the mlflow run initialization on it's own via kedro hooks. In Azure ML Pipelines, at runtime, all of the...
Right now, additional run params are passed via JSON object in command line. Kedro uses different syntax `--params param_key1:value1,param_key2:2.0` (https://kedro.readthedocs.io/en/stable/kedro_project_setup/configuration.html#specify-parameters-at-runtime). As per https://stackoverflow.com/a/70607923/1955346 it now also supports nested params, so...