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dtzar
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Restructure looks good overall!
docs/getting_started.md
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| * The second stage of the pipeline, **Train model**, triggers the run of the ML Training Pipeline. The training pipeline will train, evaluate, and register a new model. The actual computation is performed in an [Azure Machine Learning Compute cluster](https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-set-up-training-targets#amlcompute). In Azure DevOps, this stage runs an agentless job that waits for the completion of the Azure ML job, allowing the pipeline to wait for training completion for hours or even days without using agent resources. | ||
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| **Note:** If the model evaluation determines that the new model does not perform better than the previous one then the new model will not be registered and the pipeline will be cancelled. | ||
| **Note:** If the model evaluation determines that the new model does not perform better than the previous one, the new model will not be registered and the pipeline will be cancelled. |
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Please add the step which will fail, the error message, and possibly the link in the evaulate code too, so we don't get another issue filed on this topic.
dtzar
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To address feedback about some confusion when following the guide (especially to do with service connections) I have refactored the document structure.