General-purpose Gradient Boosting Library
End-to-end Open Source Platform for Machine Learning. One of the main developers of TensorFlow Estimators and Maintainer of TensorFlow I/O
Machine Learning Toolkits on Kubernetes. Co-chair of Distributed Training Working Group and maintainer of various Kubernetes operators
Unified Interface for Constructing and Managing Workflows
Kubernetes-native Deep Learning Framework with Fault-tolerance and Elastic Scheduling
Unified Interface to Visualize Popular Statistical R Packages with ggplot2 Style
R Package for Automatic Generation of Interactive Visualizations for Popular Statistical Results
R Interface to Python - Comprehensive Set of Tools for Interoperability between Python and R
R Interfaces to Core TensorFlow Components, including Estimators, Keras, and Datasets API
R Interface to Open Neural Network Exchange (ONNX)
R Package for Distance Metric Learning
R Package for Local Fisher Discriminant Analysis
JPMML-SparkML Plugin for Converting LightGBM-Spark Models to PMML
Python Package for State-of-art Metric Learning Algorithms
Tools to Automate Scaffolding R Interfaces to Packages in Other Programming Languages
Fault-tolerant Library for Deep Learning Frameworks
Collection of Useful Functions for Project Maintainers
In-memory Platform for Distributed and Scalable Machine Learning. Also authored h2o4gpu R Package.
Microsoft Machine Learning for Apache Spark
Flexible and Powerful Data Analysis / Manipulation Library for Python
Container-native Workflow Engine for Orchestrating Parallel Jobs on Kubernetes
A Bridge That Connects SQL Engines to Machine Learning Toolkits
R Package for Training Classification and Regression Models
Python Toolkit for Exploratory Data Analysis that Accelerates Data Exploration and Analysis with Automated and Polished Analysis Widgets.