Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
-
Updated
Aug 7, 2024 - Python
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
🍪 Cookiecutter template for MLOps Project. Based on: https://mlops-guide.github.io/
This is a simple webapp for wine quality prediction and involves MLOPs including DVC for model and data tracking and Github actions for CI-Cd workflows. The app is deployed on Heroku.
Project Includes python script (which runs in an MLOps environment) with the task of auto training Models until a desired accuracy is achieved.
This repository demonstrates how to set up automated model training workflows triggered by AWS S3 using Kestra. When new customer interaction data is added to S3, the system retrains recommendation models to enhance personalization. Configuring environment variables with GitHub and AWS credentials.
Small test to see how MLFLOW relates to experiment tracking with Streamlit
Add a description, image, and links to the mlops-environment topic page so that developers can more easily learn about it.
To associate your repository with the mlops-environment topic, visit your repo's landing page and select "manage topics."