Technical requirements

There are a few key terms that you may want to research before reading this chapter if you are new to ML. The definitions given here are taken verbatim from the documentation at this link: https://learn.microsoft.com/en-us/azure/machine-learning/how-to-understand-automated-ml?view=azureml-api-2#classification-metrics:

• The area under the curve (AUC): The AUC can be interpreted as the proportion of correctly classified samples. More precisely, the AUC is the probability that the classifier will rank a randomly chosen positive sample higher than a randomly chosen negative sample.
• Recall: Recall is the ability of a model to detect all positive samples.
• Precision: Precision is the ability of a model to avoid labeling negative samples as positive.

As with the previous chapters, you’ll need the following:

• FAA Wildlife Strike data files from either the FAA website or the Packt GitHub site
• A Power BI Pro license
• One of the...