Demo 3.1 Automated Machine Learning

The video tutorial provides an in-depth understanding of automated machine learning (AutoML), its inputs, and the process of running it using Azure Machine Learning Studio. It covers the creation of datasets, selection of algorithms, and evaluation metrics. The tutorial also demonstrates how to deploy and test models using Python, emphasizing the importance of choosing the right algorithm and configuration settings for optimal results.

What are the two types of datasets mentioned in the text?

Discuss the significance of the voting ensemble model mentioned in the text.

How does the normalized root mean square error help in evaluating machine learning models?

What steps are involved in deploying a machine learning model as per the text?