Popular GitHub Repositories for 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.

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

Performance of various open source GBM implementations

Sample AI Apps built with H2O Wave.

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/

Prinz provides ML integrations for Nussknacker.

Rust-based implementation of H2O mojo

My solutions for the 2023 Cloudflight Coding Contest (AI Category)

Files for compiling my presentation about H2O.ai.

AutoML-MLOps is a comprehensive platform that simplifies the machine learning workflow by automating model development, training, and deployment. With features like real-time dashboards, interactive data visualization, and automated target selection, it enables both beginners and experienced data scientists to save time and improve model accuracy.

Code Snippets - Data Science ,Machine Learning,Deep Learning,H2O,Time Series,Spark ,Big data,Azure Databricks