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.
Currently, H2O supports model training only with the H2O server running. But, due to security considerations, it is necessary to take a server-free approach where H2O is used as a library and the wrapping application can embed the model training inline. If this feature can be achieved only in a single node, that is still fine. Having a server running and listening for requests is not allowed where security is paramount.
Currently, H2O supports model training only with the H2O server running. But, due to security considerations, it is necessary to take a server-free approach where H2O is used as a library and the wrapping application can embed the model training inline. If this feature can be achieved only in a single node, that is still fine. Having a server running and listening for requests is not allowed where security is paramount.