42.40. Data Science project using Azure ML SDK

42.40.1. Instructions

We saw how to use the Azure ML platform to train, deploy and consume a model with the Azure ML SDK. Now look around for some data that you could use to train another model, deploy it and consume it. You can look for datasets on Kaggle and Azure Open Datasets.

42.40.2. Rubric

Exemplary	Adequate	Needs Improvement
When doing the AutoML Configuration, you went through the SDK documentation to see what parameters you could use. You ran a training on a dataset through AutoML using Azure ML SDK, and you checked the model explanations. You deployed the best model and you were able to consume it through the Azure ML SDK.	You ran a training on a dataset through AutoML using Azure ML SDK, and you checked the model explanations. You deployed the best model and you were able to consume it through the Azure ML SDK.	You ran a training on a dataset through AutoML using Azure ML SDK. You deployed the best model and you were able to consume it through the Azure ML SDK.

42.40.3. Acknowledgments

Thanks to Microsoft for creating the open-source course Data Science for Beginners. It inspires the majority of the content in this chapter.