Popular GitHub Repositories for H2o

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

Tutorials and training material for the H2O Machine Learning Platform

This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.

A curated list of research, applications and projects built using the H2O Machine Learning platform

R package for automation of machine learning, forecasting, model evaluation, and model interpretation

Analytics & Machine Learning R Sidekick

An End-to-End Implementation of AutoML with H2O, MLflow, FastAPI, and Streamlit for Insurance Cross-Sell

ForestFlow is a policy-driven Machine Learning Model Server. It is an LF AI Foundation incubation project.

RSparkling: Use H2O Sparkling Water from R (Spark + R + Machine Learning)

A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python

Forecasting with H2O AutoML. Use the H2O Automatic Machine Learning algorithm as a backend for Modeltime Time Series Forecasting.

D2C(Data-driven Control Library) is a library for data-driven control based on reinforcement learning.

This repository covers h2o ai based implementations

Wave App for H2O AutoML

MLflow-tracking server example with Minio and H2O

Production ready templates for deploying Driverless AI (DAI) scorers. https://h2oai.github.io/dai-deployment-templates/

Presentación, código y ejemplos del Machine Learning Spain XXVII

Benchmark of current ML automation frameworks