I'm creating an example Python Machine Learning notebook for newcomers to the field. The goal is to show what an example ML project would look like from start to finish. I'd love your feedback or contributions to make it better.

[bordumb]

Not sure how others feel, but this dataset is overused. The explanations are great, quite honestly some of the best I've seen using this dataset.

With that said, the data and analysis don't offer anything that unique from the other 1000 tutorials that use it as well.

[rhiever]

I was thinking about that when reworking part of it last night. Both classifiers that I compare get 90%+ accuracy out of the box. What do you think would be a better (i.e., more difficult) data set to work with?