Open Source Fast Scalable Machine Learning Platform For Smarter Applications (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), ...)
data.table for Python
H2Oai GPU Edition
Web based interactive computing environment for H2O
Sparkling Water provides H2O functionality inside Spark cluster
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
H2O Cloud code.
Tutorials and training material for the H2O Machine Learning Platform
Library of different Jenkins pipeline building blocks.
Build, manage and deploy H2O's high-speed machine learning models.
Integrating H2O-3 AutoML with Amazon Sagemaker
A curated list of research, applications and projects built using H2O Machine Learning
RSparkling: Use H2O Sparkling Water from R (Spark + R + Machine Learning)
Presentations from H2O meetups & conferences by the H2O.ai team
Deep Learning in H2O using Native GPU Backends
Machine Learning Interpretability Resources
Templates for projects based on top of H2O.
Python 2.7 & 3.5+ runtime type-checker
Python 3 Bindings for NVML library. Get NVIDIA GPU status inside your program.
Python module to interface with OpenML
Intel® Data Analytics Acceleration Library (Intel® DAAL)
scikit-learn: machine learning in Python
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