h2oai

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.

Presentations from H2O meetups & conferences by the H2O.ai team

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

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

Deep Learning UDF for KSQL for Streaming Anomaly Detection of MQTT IoT Sensor Data

Performance of various open source GBM implementations

Sample AI Apps built with H2O Wave.

Showcase for using H2O and R for churn prediction (inspired by ZhouFang928 examples)

Showcase for using H2O and R for scoring for marketing campaign in retail

Contains benchmarking and interpretability experiments on the Adult dataset using several libraries

Wave App for H2O AutoML

This repository covers h2o ai based implementations

R functions for project setup, data cleaning, machine learning, SuperLearner, parallelization, and targeted learning.

Shapley Values with H2O AutoML Example (ML Interpretability)

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

MLflow-tracking server example with Minio and H2O

Analyzing customer attrition & strategies to reduce churn via AutoML techniques & PowerBI

Explains machine learning models fast using the Anchor algorithm originally proposed by marcotcr in 2018

Diverse collection of 100 Hydrogen Torch Use-Cases by different industries, data-types, and problem types