mlflow-model

MLflow Multi-Tenancy & Governance Gateway adds tenant isolation, access control and audit logging to self-hosted MLflow without modifying MLflow itself. Designed for Kubernetes, private cloud and regulated environments where SaaS ML platforms are not an option.

MATLAB® interfaces to MLflow™ Tracking and MLflow Model Logging.

MLOps with model deployment using docker and scaling using kubernetes; API deployment with FastAPI; using MLFlow for model tracking for water potability dataset

Les entreprises perdent chaque année des clients sans toujours comprendre pourquoi. Ce projet vous permettra de suivre et gérer le churn grâce à MLflow, en versionnant les modèles et visualisant les métriques pour améliorer la fidélisation et le revenu client.

Walk through getting the baseline model up to a proper implementation while gradually increasing the number of tracked objects.

A hands-on MLflow project demonstrating experiment tracking, model training, and lifecycle management using Scikit-learn, XGBoost, and Dagshub integration.

CentraleSupélec/OpenClassrooms Data Scientist 2024-2025 - Projet 7 (EDA & modélisation seules)

An end-to-end machine learning project for predicting house prices using the Ames Housing dataset. Built with clean software engineering principles, featuring a modular architecture powered by Strategy, Factory, and Template Method design patterns, and orchestrated end to end with ZenML and MLflow.

Project looks to create a stand-alone MLflow model registry which sits on its own Azure Container Registry, using an image, connected to a blob storage (artifact store) and internal sqlite db (registry store).

End-to-end MLOps pipeline featuring modular data loading, model training, evaluation, and experiment tracking with MLflow and SQLite.

Build end-to-end DL pipeline for computer vision (Image classification) for “Chest Disease Classification from Chest CT Scan Images” and deploy Flask web app to AWS EC2 with Docker and CI/CD tool: Jenkins

Production-style ML workflow demonstrating MLflow experiment tracking, model registry, and deployment via a Streamlit sentiment analysis app.

A sample container of Mlflow/Python for deployment to AWS Lambda for ML model serving.

End-to-end machine learning pipeline for customer churn prediction on imbalanced data. Includes ADASYN oversampling, DVC for version control, and MLflow for experiment tracking and model management.