intro-to-pipelines

Introduction to Azure Machine Learning Pipelines

The following notebooks provide an introduction to a concept in Azure Machine Learning Pipelines. They will introduce you to core Azure Machine Learning Pipelines features. These notebooks below are designed to go in sequence.

1. aml-pipelines-getting-started.ipynb: Start with this notebook to understand the concepts of using Azure Machine Learning Pipelines. This notebook will show you how to runs steps in parallel and in sequence.
2. aml-pipelines-with-data-dependency-steps.ipynb: This notebooks shows how to connect steps in your pipeline using data. Data produced by one step is used by subsequent steps to force an explicit dependency between steps.
3. aml-pipelines-publish-and-run-using-rest-endpoint.ipynb: Once you are satisfied with your iterative runs in, you could publish your pipeline to get a REST endpoint which could be invoked from non-Pythons clients as well.
4. aml-pipelines-data-transfer.ipynb: This notebook shows how you transfer data between supported datastores.
5. aml-pipelines-use-databricks-as-compute-target.ipynb: This notebooks shows how you can use Pipelines to send your compute payload to Azure Databricks.
6. aml-pipelines-use-adla-as-compute-target.ipynb: This notebook shows how you can use Azure Data Lake Analytics (ADLA) as a compute target.
7. aml-pipelines-how-to-use-estimatorstep.ipynb: This notebook shows how to use the EstimatorStep.
8. aml-pipelines-parameter-tuning-with-hyperdrive.ipynb: HyperDriveStep in Pipelines shows how you can do hyper parameter tuning using Pipelines.
9. aml-pipelines-how-to-use-azurebatch-to-run-a-windows-executable.ipynb: AzureBatchStep can be used to run your custom code in AzureBatch cluster.
10. aml-pipelines-setup-schedule-for-a-published-pipeline.ipynb: Once you publish a Pipeline, you can schedule it to trigger based on an interval or on data change in a defined datastore.
11. aml-pipelines-with-automated-machine-learning-step.ipynb: AutoMLStep in Pipelines shows how you can do automated machine learning using Pipelines.
12. aml-pipelines-setup-versioned-pipeline-endpoints.ipynb: This notebook shows how you can setup PipelineEndpoint and submit a Pipeline using the PipelineEndpoint.
13. aml-pipelines-showcasing-datapath-and-pipelineparameter.ipynb: This notebook showcases how to use DataPath and PipelineParameter in AML Pipeline.
14. aml-pipelines-how-to-use-pipeline-drafts.ipynb: This notebook shows how to use Pipeline Drafts. Pipeline Drafts are mutable pipelines which can be used to submit runs and create Published Pipelines.
15. aml-pipelines-hot-to-use-modulestep.ipynb: This notebook shows how to define Module, ModuleVersion and how to use them in an AML Pipeline using ModuleStep.