H2O

About H2O

A fast, scalable, open-source machine learning and artificial intelligence platform. H2O supports widely used statistical and machine learning algorithms including gradient boosted machines, random forests, deep learning, and more with Python and R APIs.

Key Features

• 1Distributed in-memory ML platform supporting R, Python, and Java APIs
• 2AutoML automatically trains and tunes hundreds of models in parallel
• 3Supports GBM, Random Forest, Deep Learning, GLM, and XGBoost algorithms
• 4H2O Flow browser-based interface for no-code model building
• 5MOJO model export for low-latency, Java-based production scoring

How Python Data Engineers Use H2O

Python data engineers use the `h2o` Python package to run distributed AutoML experiments on large training datasets that exceed single-machine memory. Engineers call `h2o.automl.H2OAutoML().train()` pointing at an H2OFrame backed by a cluster, let H2O evaluate dozens of algorithms, then export the best model as a MOJO for deployment in a Python scoring service.