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H2O ML Python cheatsheet OR Comparison between H2O's Python API and scikit-learn

I wanted to ask if anyone has come across a h2o machine learning python cheatsheet or comparison between h2o using python and scikit-learn

Would be very helpful since I am a scikit-learn guy.

Solution
    • There is a H2OFrame / Pandas DataFrame munging cheatsheet here.
    • The "EEG Eyestate" demo was written for both H2O and Scikit-learn, so that's the closest thing to a side-to-side comparison that I can point you to.
    • There are some Python tutorials here, which demonstrate basic usage of the supervised H2O algos (and grid search) in Python.
    • Taylor Smith created the skutil module which allows you to use H2O models more easily with sklearn pipelines.