Hi r/machinelearning!

One thing that has always bugged me in my classes is that we’re constantly using different sets for everything, and I feel like it’d be illuminating if I picked a few comprehensive set and did everything possible on each of them.

I feel like this way you could use a amount of techniques on one data set and see very clearly their strengths and weaknesses against each other.

What do you folks think? Or is there a good reason for changing the data set per technique?

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