santiagxf / trunkbased-mlopsLinks
This repository showcases how to implement trunk-based development workflow while working in a Machine Learning project.
☆40Updated 2 years ago
Alternatives and similar repositories for trunkbased-mlops
Users that are interested in trunkbased-mlops are comparing it to the libraries listed below
Sorting:
- Template for getting started with automated ML Ops on Azure Machine Learning☆129Updated 3 years ago
- Guided accelerator consolidating best practice patterns, IaaC and AML code artefacts to provide a reference approach to implementing MLOp…☆49Updated last year
- Support ML teams to accelerate their model deployment to production leveraging Azure☆91Updated last year
- Providing tools and templates to facilitate modern MLOps practices☆85Updated last year
- MLOps practices using Azure ML service with Python SDK and Databricks for model training☆47Updated 5 years ago
- ☆195Updated 2 years ago
- Prescriptive MLOps scenarios for building, deploying and monitoring machine learning models with Azure Machine Learning.☆15Updated last year
- Azure Databricks MLOps sample for Python based source code using MLflow without using MLflow Project.☆91Updated 5 months ago
- Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.☆132Updated 3 months ago
- Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.☆78Updated last year
- Managing Data and Model Drift with Azure Machine Learning☆45Updated 2 years ago
- Modular and minimalistic MLOps recipes☆70Updated 5 years ago
- ML Ops demo for Azure Databricks and Azure ML SDK☆21Updated 5 years ago
- A workshop for doing MLOps on Azure Machine Learning☆35Updated 3 years ago
- Turning AML compute into Ray cluster☆18Updated 2 years ago
- Azure plugins for Feast (FEAture STore)☆82Updated last year
- Example Azure Pipeline to train and deploy a machine learning model using the Azure Machine Learning service☆114Updated 3 years ago
- Scalable solution for ML Observability☆36Updated last year
- ☆23Updated last year
- An example repo for provisioning a complete Azure Machine Learning environment through Terraform☆24Updated 2 years ago
- GitHub Action that allows you to attach, create and scale Azure Machine Learning compute resources.☆20Updated 3 years ago
- MLOps using Azure Databricks, Azure DevOps and Azure ML Services☆56Updated 4 years ago
- Turning AML compute into Ray cluster☆77Updated 2 years ago
- ☆19Updated 3 years ago
- A template repository for quickly adopting Azure Machine Learning☆27Updated 3 years ago
- Private Preview: Responsible AI Tooling in Azure Machine Learning☆18Updated 3 years ago
- under renovation☆31Updated 2 years ago
- This repo demonstrates GitHub actions to build and deploy your ML application☆35Updated last year
- Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.☆579Updated last year
- this is a python framework that helps to build any data engineering and data science solutions in Databricks☆14Updated 2 years ago