https://github.com/revodavid/RMLops

MLOps with R and Azure Pipelines
https://github.com/revodavid/RMLops

Last synced: 5 months ago
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MLOps with R and Azure Pipelines

• Host: GitHub
• URL: https://github.com/revodavid/RMLops
• Owner: revodavid
• License: mit
• Created: 2019-06-27T16:46:49.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2021-01-05T00:04:10.000Z (over 4 years ago)
• Last Synced: 2024-11-16T08:14:44.379Z (5 months ago)
• Language: R
• Size: 2.72 MB
• Stars: 37
• Watchers: 4
• Forks: 22
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• jimsghstars - revodavid/RMLops - MLOps with R and Azure Pipelines (R)

README

        
[![Build Status](https://dev.azure.com/davidsmi0786/davidsmiRtest/_apis/build/status/revodavid.RMLops?branchName=master)](https://dev.azure.com/davidsmi0786/davidsmiRtest/_build/latest?definitionId=1&branchName=master)

# RMLops: A simple R example for Azure Pipelines

This is the Github repository associated with this Azure Pipelines project: https://dev.azure.com/davidsmi0786/davidsmiRtest. It is intended as a simple example

of using R with Azure Pipelines to use a CI/CD process to trigger training of a

predictive model.

You will need an Azure Subscription to replicate these examples. For new subscribers, [use this link for an Azure Account](https://azure.microsoft.com/free/?WT.mc_id=rmlops-github-davidsmi) that includes $200 of Azure services.

## Presentations

Slides from the presentation [A DevOps process for deploying R to production](https://github.com/revodavid/RMLops/blob/master/earl2019slides.pdf) are available. Presented at the [EARL 2019 conference](http://www.earlconf.com/) in London, September 11 2019.

Slides from the presentation [A DevOps process for deploying R to production](https://github.com/revodavid/RMLops/blob/master/user2019slides.pdf) are available. Presented at the [useR!2019 conference](http://www.user2019.fr/) in Toulouse, July 12 2019. A [video recording](https://youtu.be/o6sIB0MJyOs) of this presentation is available.

## Resources

[Integrating the Data Science and App Development Cycles](https://aka.ms/AA5ib6c) (Medium), Francesca Lazzeri, Microsoft. 

[MLOps: Manage, deploy, and monitor models with Azure Machine Learning Service](https://aka.ms/mlopsdoc) (Microsoft Docs).  

[Train and deploy machine learning models with Azure Pipelines](https://aka.ms/azpipe) (Microsoft Docs). 

[Azure Machine Learning Service](https://aka.ms/amlsvc) (Microsoft Docs).