Summary

In this chapter, you learned how to apply AutoML in Azure to a classification problem and a time series prediction problem. You were able to build a model within the Azure Machine Learning environment with an Azure notebook and via JupyterLab. You then understood how the entire workspace relates to the experiments and runs. You also see the visualization during these automated runs; this is where feature importance, the global and local impact of features, and explanations based on raw and engineered features provide an intuitive understanding. Besides your affinity with a tool, it is also important that the platform aligns with your enterprise roadmap. Azure is an overall great platform with a comprehensive set of tools, and we hope you enjoyed exploring its automated ML capabilities.