Execute Azure Machine Learning pipelines in Azure Data Factory or Synapse Analytics

Learn how to run your Azure Machine Learning pipelines as a step in your Azure Data Factory or Synapse Analytics pipelines.
Azure Machine Learning Pipeline Video:
• Azure Machine Learning...
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[@mariaakbarpour902]

First part of your videos is really funny :)) .Keep going 👍

[@MG_cafe]

Thanks Maria and hope you enjoyed it!

[@arvinddige5323]

Great content, thanks MG

[@anthony281190]

16:53 What is the different with Pipiline endpointID and Pipiline ID? In my case, my Machine Learning Execute Failed with Pipeline ID

[@anony124]

as i see in this video you are not getting the output of data lake storage to the input of the AML Pipeline , you just trigger the pipeline when the data ingest is successful , but how we can input data from data lake to the AML pipeline and train the model on that data ?

[@Weallgoingtodiesomeday]

Great content Keep On 👏 my issue is with machine learning data path assignment is not automatically updated

[@akrsrivastava]

I am facing similar issue. The pipeline is always running the training with the same dataset which was used to build and publish it. It is not picking up the latest training data. Needed some help

[@jadis9086]

Hello Makram. Did you find a solution ?

[@Weallgoingtodiesomeday]

@@jadis9086 I raised this issue as a support request to the Microsoft Azure team they said it's a bug and they would fix it soon

[@koffiegast]

@@Weallgoingtodiesomeday Is it fixed? Being able to dynamically change input/output paths would be a really necessary.