MLOps with Azure ML

added toggle for evaluation step (#152)

  # These are the default values set in ml_service\util\env_variables.py. Uncomment and override if desired.
RUN_EVALUATION=true
ALLOW_RUN_CANCEL=true

MLOps with Azure ML

117766

Discover scoring model + Add Swagger endpoint to scoring container (#…

MLOps with Azure ML

117491

Change folder structure to support several training pipelines and mod…

MLOps with Azure ML

116966

fix sources_directory_train variable name (#146)

MLOps with Azure ML

116905

Added notebooks for training and scoring a Diabetes Ridge regression …

MLOps with Azure ML

116799

extending use of SOURCES_DIR_TRAIN variable (#143)

MLOps with Azure ML

Use training data from a managed datasource (#134)

* Data from managed datastore

* merge with unassigned variable fix

* bugfix

* typo

* linting

* linting

* linting

* added a link to az cli

* doc update

* reregistering a dataset

* typo

* rephrasing

* rephrasing

* auth enabled

* revert auth enabled

MLOps with Azure ML

Fixed assignment bug for build_uri (#133)

If the builduri_base is None, the build_uri would never been instantiated causing an error when calling register_aml_model(model_name, exp, run_id, build_id, build_uri). By adding the else statement, this is prevented.

MLOps with Azure ML

112351

Tag the experiment runs and model with a link to the build ui (#132)

MLOps with Azure ML

110210

Making clarifications in Getting Started guide (#131)