production-machine-learning

Here are 5 public repositories matching this topic...

katonic-dev / explainit

A modern, enterprise-ready business intelligence web application

python data-science machine-learning pandas-dataframe data-visualization production-machine-learning mlops drift-detection model-monitoring machine-learning-operations

Updated Dec 9, 2022
Python

modzy / sdk-python

Star

Python library for Modzy Machine Learning Operations (MLOps) Platform

python docker machine-learning microservices deployment api-client model-deployment model-serving serving explainable-ai production-machine-learning ai-security mlops kuberenetes drift-detection machine-learning-operations

Updated Sep 8, 2023
Python

Kronbii / thermal-super-resolution

Star

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

real-time research computer-vision deep-learning cuda pytorch thermal-imaging super-resolution real-time-processing image-enhancement production-machine-learning imdn model-optimization

Updated Oct 10, 2026
Python

ilyas-hassan / biotech-intel

Star

Production-grade ML platform for biotech research intelligence. Multi-agent RAG system with LangGraph for discovering papers, companies, and funding. Features semantic search, knowledge graphs, and full MLOps stack. Built to showcase end-to-end ML/AI engineering skills.

python docker kubernetes machine-learning natural-language-processing artificial-intelligence data-engineering knowledge-graph named-entity-recognition semantic-search multi-agent-systems production-machine-learning rag mlops fastapi vector-database langchain langgraph

Updated Jan 16, 2026
Python

akshayDev17 / ML-Engineer

Star

Self-study course on designing production ML systems: 18 modules from data quality and feature pipelines to serving, monitoring and drift, plus lead-level interview quizzes and a runnable end-to-end churn project (PyTorch, Optuna, ONNX, FastAPI).

machine-learning data-validation scikit-learn pytorch machine-learning-engineering model-serving onnx production-machine-learning mlops feature-store optuna model-monitoring data-drift ml-system-design

Updated Oct 13, 2026
Python

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