From f1160f354b87047ca9979a06798e62007934ae39 Mon Sep 17 00:00:00 2001 From: Angel Mendez Date: Fri, 7 Oct 2022 12:19:26 -0500 Subject: [PATCH] feat: Add file content to translate --- .../18-Low-Code/translations/assignment.es.md | 11 +++++++++++ 1 file changed, 11 insertions(+) create mode 100644 5-Data-Science-In-Cloud/18-Low-Code/translations/assignment.es.md diff --git a/5-Data-Science-In-Cloud/18-Low-Code/translations/assignment.es.md b/5-Data-Science-In-Cloud/18-Low-Code/translations/assignment.es.md new file mode 100644 index 00000000..c826bb2b --- /dev/null +++ b/5-Data-Science-In-Cloud/18-Low-Code/translations/assignment.es.md @@ -0,0 +1,11 @@ +# Low code/No code Data Science project on Azure ML + +## Instructions + +We saw how to use the Azure ML platform to train, deploy and consume a model in a Low code/No code fashion. Now look around for some data that you could use to train an other model, deploy it and consume it. You can look for datasets on [Kaggle](https://kaggle.com) and [Azure Open Datasets](https://azure.microsoft.com/services/open-datasets/catalog?WT.mc_id=academic-77958-bethanycheum&ocid=AID3041109). + +## Rubric + +| Exemplary | Adequate | Needs Improvement | +|-----------|----------|-------------------| +|When uploading the data you took care of changing the feature's type if necessary. You also cleaned the data if needed. You ran a training on a dataset through AutoML, and you checked the model explanations. You deployed the best model and you were able to consume it. | When uploading the data you took care of changing the feature's type if necessary. You ran a training on a dataset through AutoML, you deployed the best model and you were able to consume it. | You have deployed the best model trained by AutoML and you were able to consume it. |