Generalized Linear Models on H2O

We’ll go over the list of features and how to use them to find the best model in shortest time.
In particular, we’ll look at selecting the right regularization and solver when dealing with large high cardinality data.
We’ll go over examples of common glm applications such as logistic regression on larger datasets.
We will demonstrate how we can use h2o.interactions and data munging to clean the data and generate new features to improve our model.