AI News, Comparing supervised learning algorithms

Comparing supervised learning algorithms

In the data science course that I instruct, we cover most of the data science pipeline but focus especially on machine learning.

Near the end of this 11-week course, we spend a few hours reviewing the material that has been covered throughout the course, with the hope that students will start to construct mental connections between all of the different things they have learned.

decided to create a game for the students, in which I gave them a blank table listing the supervised learning algorithms we covered and asked them to compare the algorithms across a dozen different dimensions.

realize that the characteristics and relative performance of each algorithm can vary based upon the particulars of the data (and how well it is tuned), and thus some may argue that attempting to construct an 'objective' comparison is an ill-advised task.

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