H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Current lambda_search will try 100 lambda values equally spaced in the log scale.
Michalk suggests to look into trying less values but do it in a coarse to fine scale.
I thought about it and thinks it is worthwhile to look into.