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.

Open-source reference monorepo for end-to-end MLOps on Snowflake, centered around Snowflake-native MLOps tooling (Feature Store, Model Registry, Tasks) in a hub-spoke layout. Questions, issues, or ideas about Snowflake ML in general are warmly welcomed.

🍪 Cookiecutter template for MLOps Project. Based on: https://mlops-guide.github.io/

Research-first machine learning experiment tracker for comparing model metrics, scalar curves, artifacts, and experiment lineage.

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.

GitHub Actions is a continuous integration and continuous delivery [CI/CD] platform that allows you to automate your build, test, and deployment pipeline. You can create workflows that build and test every pull request to your repository, or deploy merged pull requests to production.

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.

Testing ZenML

Testing Kedro

Testing flyte

🤖 AI-powered tools to automate DevOps workflows: intelligent log analysis, PR review assistant, pipeline optimization, and anomaly detection using LLMs

🤖 ML pipeline to predict sneaker prices from stock values.

Small test to see how MLFLOW relates to experiment tracking with Streamlit

A local simulation setup showcasing a basic MLOps Workflow for DevOps to learn into MLOps

A Workbench for Machine Learning, our origins are in computer vision so we've prioritized this first, with more functionalities and compatibilities coming regularly. Aurora: make models, that make AI.

Predict sneaker prices by validating, cleaning, training, and predicting data with a reproducible machine learning pipeline powered by DVC.

🚀 Build and deploy machine learning models with this MLOps project template, designed for easy integration and effective monitoring in production environments.