A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

Code For The Issue Label Bot, an App that automatically labels issues using machine learning, available on the GitHub Marketplace. This is also code for the blog article: "How to automate tasks on GitHub with machine learning for fun and profit"

⚓ Eurybia monitors model drift over time and securizes model deployment with data validation

Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in production.

A modern, enterprise-ready business intelligence web application

Python library for Modzy Machine Learning Operations (MLOps) Platform

The official JavaScript SDK for the Modzy Machine Learning Operations (MLOps) Platform.

The official Java library for the Modzy Machine Learning Operations (MLOps) Platform

The Golang library for Modzy Machine Learning Operations (MLOps) Platform

Sharing my journey to be fluent in writing machine learning models for interesting datasets from competitions from kaggle , AICrowd and other ensemble of deep learning model techniques and then trying to get them to production.

End to end machine learning models deployment to production for a bank marketing problem.

ProductionML.{org,com} website

First thermal super-resolution system to achieve 34.2 dB PSNR at 229+ FPS using novel IMDN architecture with specialized thermal adaptations. Features breakthrough RGB→thermal transfer learning, thermal-aware multi-component loss, and real-time inference (2x: 270.6 FPS, 3x: 256.1 FPS, 4x: 250.9 FPS). Production-ready PyTorch + CUDA implementation