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...)
Sparkling Water provides H2O functionality inside Spark cluster
Library of different Jenkins pipeline building blocks.
H2Oai GPU Edition
Presentations from H2O meetups & conferences by the H2O.ai team
A curated list of research, applications and projects built using H2O Machine Learning
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
Tutorials and training material for the H2O Machine Learning Platform
Build, manage and deploy H2O's high-speed machine learning models.
Intel® Data Analytics Acceleration Library (Intel® DAAL)
Web based interactive computing environment for H2O
H2O Cloud code.
Deep Learning in H2O using Native GPU Backends
Templates for projects based on top of H2O.
RSparkling: Use H2O Sparkling Water from R (Spark + R + Machine Learning)
Python 2.7 & 3.5+ runtime type-checker
scikit-learn: machine learning in Python
Python 3 Bindings for NVML library. Get NVIDIA GPU status inside your program.
CUB is a flexible library of cooperative threadblock primitives and other utilities for CUDA kernel programming.
Example of putting a mojo zip file as a resource into a java servlet.
Log Analysis Use Case for PyData2016
A common bricks library for building scalable and portable distributed machine learning.
kmeans clustering with multi-GPU capabilities
Meetup Hackathon 06/21/2017
Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA