Project Idea after Supervised ML: Regression and Classification course


I have just finished Supervised ML: Regression and Classification course, I have done all the assignments for it, but I still feel like I need to do a small project on it from scratch to get used to concepts in code better.

Any ideas and is what I am thinking about beneficial?

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There are some datasets available on a site run by UC Irvine that are good to practice with
I suggest finding a dataset that’s interesting and trying what you’ve learned on them.

Hope this helps!

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I’ll suggest you first do a crash course from YouTube(freecodecamp) regarding Sklearn just to get a good idea about hyperparameter tuning, pipelines etc. Then fetch some datasets from There are 1000s of datasets available for regression and classification for you to practice on.

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