Predicting restaurant inspection failures

This year I ramped up the amount of machine learning I covered in my fall class at Penn. For the final project, I had my students recreate the phenomenally creative restaurant health inspection prediction project from Chicago. There were two components of the project – the development of a predictive model and then the design of an application to convert the predictive intelligence into a application that the health department could use to better allocate its limited inspection resources.

The students don’t estimate models anymore complicated than logistic regression, but they do spend a great deal of time constructing training and test sets and validating their models.

Below is a video from two of the students in the class, Shruthi Arvind and Kristen Coe, presenting their health inspection app. Here is a link to their report (PDF) which gives a more technical description of the project.

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