H2O.ai
- Mountain View, CA
- http://h2o.ai
- h2ostream@googlegroups.com
Grow your team on GitHub
GitHub is home to over 50 million developers working together. Join them to grow your own development teams, manage permissions, and collaborate on projects.
Sign up
Pinned repositories
Repositories
-
sparkling-water
Sparkling Water provides H2O functionality inside Spark cluster
-
h2o-3
Open Source Fast Scalable Machine Learning Platform For Smarter Applications: Deep Learning, Gradient Boosting & XGBoost, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
-
-
datatable
A Python package for manipulating 2-dimensional tabular data structures
-
driverlessai-recipes
Recipes for Driverless AI
-
tutorials
This is a repo for all the tutorials put out by H2O.ai. This includes learning paths for Driverless AI, H2O-3, Sparkling Water and more...
-
driverlessai-tutorials
H2OAI Driverless AI Code Samples and Tutorials
-
py-repo
Python package repository
-
h2o-kubernetes
A command-line tool to ease deployment (and undeployment) of H2O open-source machine learning platform H2O-3 to Kubernetes.
-
awesome-h2o
A curated list of research, applications and projects built using the H2O Machine Learning platform
-
xgboost
Forked from dmlc/xgboostScalable, 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
-
-
dai-deployment-templates
Production ready templates for deploying Driverless AI (DAI) scorers.
-
db-benchmark
reproducible benchmark of database-like ops
-
h2o-flow
Web based interactive computing environment for H2O
-
H2O-LightGBM-CUDA
Forked from bordaw/H2O-LightGBM-CUDACUDA Implementation for the H2O version of the LightGBM package
-
-
dai-deployment-examples
Examples for deploying Driverless AI (DAI) scorers.
-
h2o-tutorials
Tutorials and training material for the H2O Machine Learning Platform
-
LightGBM
Forked from microsoft/LightGBMA fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.
-
-
mojoland
Testing ground to ensure mojos backward compatibility
-
-
-
-
-
-