Sparkling Water provides H2O functionality inside Spark cluster
Deep Learning in H2O using Native GPU Backends
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
Open Source Fast Scalable Machine Learning API For Smarter Applications (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles...)
kmeans clustering with multi-GPU capabilities
Meetup Hackathon 06/21/2017
Presentations from H2O meetups & conferences by the H2O.ai team
RSparkling: Use H2O Sparkling Water from R (Spark + R + Machine Learning)
A curated list of research, applications and projects built using H2O Machine Learning
Tutorials and training material for the H2O Machine Learning Platform
Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA
Build, manage and deploy H2O's high-speed machine learning models.
Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, HyperLogLogs, Bitmaps.
Web based interactive computing environment for H2O
Optimized primitives for collective multi-GPU communication (with Windows / Visual Studio capability)
H2O Cloud code.
Templates for projects based on top of H2O.