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Predicting MO with H2O Models from IRDA data
H2O is a powerful tools to have a general idea of the performance of different models.
Machine Learning, Spatial Data Analysis, and so much more
H2O is a powerful tools to have a general idea of the performance of different models.
I recently prepare FADQ data to make some predictives models. Those are great spatial data, but I can’t go without a bit of soil information.
I will list here all the little snipset of code that I look up all the time.
I now know how to use this beautiful tool.
I have a lot of things to try… so I need a lot of data to play with. Here I summarize you how I extract FADQ historic data. I’m going to place the tidy data in a repro on github and play with it for my next blogs.