ezwiefel / aml-mlops-mlflow Goto Github PK
View Code? Open in Web Editor NEWMLOps in Azure Machine Learning using MLFlow and XGBoost in training code
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sanjiny3000backupaml-mlops-mlflow's Issues
Add more polish to README.md
Add prereqs to README.md
- Create Workspace(s)
- Set GH Actions
- Etc.
Add architectural diagram or explanation
Add tests of train.py
Add filename filters to lint, train, and test workflow
As we layer in scoring/deployment tools, we don't need to retrain the model when changing non-training related code
make config fails with missing azureml-dataprep package
Issue with missing azureml-dataprep package when running make config
Reported by @azeltov:
(base) azeltov@DESKTOP-D59GBAK:~/git/aml-mlflow-xgb$ make config
az ml datastore attach-blob -c diabetes -a publicmldatasc -n diabetes --sas-token "?si=DiabetesReadOnly&sv=2019-10-10&sr=c&sig=cz9P%2B1V1eC6FvDIKBQNmA5nWqbsGfkqzdPTTYmiidfg%3D"
{"account_name": "publicmldatasc", "container_name": "diabetes", "datastore_type": "AzureBlob", "endpoint": "core.windows.net", "name": "diabetes", "protocol": "https" }
az ml dataset register -f aml/datasets/diabetes-table.json
Cannot perform validation due to missing required package "azureml-dataprep", which can be installed by running: "/opt/az/bin/python3" -m pip install azureml-dataprep --upgrade. This can also be resolved by setting --skip-validation.
Makefile:6: recipe for target 'register-data' failed make: *** [register-data] Error 1Add Model Training Action
The model training action should be run on PR (or push?) to Develop or Main Branches - with the difference being the environment that it's running in (which changes the GH secret used for login)
Change name of database-files.json and database-table.json
We're using _ everywhere else... let's be consistent
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GH Actions: on: workflow_run is not triggering as expected
I didn't look into this too much, but it appears to be a limitation of GH.
https://github.community/t/triggering-a-new-workflow-from-another-workflow/16250/21
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