45 Open source projects that are alternatives of or similar to mercury-ml

Relational data pipelines for the science lab

NOTE: skutil is now deprecated. See its sister project: https://github.com/tgsmith61591/skoot. Original description: A set of scikit-learn and h2o extension classes (as well as caret classes for python). See more here: https://tgsmith61591.github.io/skutil

Exemplary, annotated machine learning pipeline for any tabular data problem.

Checks-Out pull request approval system

Identifying diseases in chest X-rays using convolutional neural networks

A simple guide to understand Prefect and make it work with your own docker-compose configuration.

minimal example implementations for bioinformatics workflow managers

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

JS Library to present and edit workflows as SVG

Hera is an Argo Workflows Python SDK. Hera aims to make workflow construction and submission easy and accessible to everyone! Hera abstracts away workflow setup details while still maintaining a consistent vocabulary with Argo Workflows.

Project maintainance tool for GitHub repositories

Materials for GWU DNSC 6279 and DNSC 6290.

R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.

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.).

Comparison tools

Tutorials and training material for the H2O Machine Learning Platform

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

Deep Learning UDF for KSQL, the Streaming SQL Engine for Apache Kafka with Elasticsearch Sink Example

docker files for h2o http2 webserver

Verteego Data Suite

Sparkling Water provides H2O functionality inside Spark cluster

A curated list of gradient boosting research papers with implementations.

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.

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.

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

H2O.ai Machine Learning Interpretability Resources

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

cuDF - GPU DataFrame Library

Access log profiler based on response time

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

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

Statistical Learning & Data Mining IV - H2O Presenation & Tutorial

DEPRECATED Build, manage and deploy H2O's high-speed machine learning models.

Python binding for the H2O HTTP server

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

Curated list of resources about Apache Airflow

Temporal service

Conductor is a microservices orchestration engine.

Scientific workflow management

Goobi workflow - Workflow management software for digitisation projects used in more than 70 cultural heritage institutions in at least 17 countries.

Workflow Management for Biomedical exploration

Source code for ArcGIS Workflow Manager JavaScript viewer - Manage your workflows on the web.

A lightweight Java based orchestration engine

Minimal Workflow orchestrator for AWS Step Functions

a web system to allow users to automatically record history and manage complicated scientific workflows in web browsers involving the online spatial data facilities, high-performance computation platforms, and open-source libraries.