Building Scalable, Secure and Responsible AI Solutions in Azure

Organizations are evolving and are becoming AI driven organisations.

This repo aims to help Data Science teams to build Scalable, Secure and Responsible AI Solutions in Azure.

PDF Slides: Building Scalable, Secure and Responsible AI Solutions in Azure

Youtube link: https://www.youtube.com/watch?v=DPRj9tGWpuM&t=31s

The AI journey can be divided into 2 parts:

1. Experimentation
2. Production

Most of the companies are in the experimentation phase, but some are in the production phase.

For the companies in the Production phase it is important to invest time to understand important topics like:

• AI/ML Platform
• MLOps
• Responsible AI
• AI/ML Security

Here are some links to help your Data Science team:

MLOps

MLOps explained | Machine Learning Essentials https://www.youtube.com/watch?v=ZVWg18AXXuE

MLOps Using Azure Machine Learning https://www.youtube.com/watch?v=uKryRn6v0w8

Azure MLOps - DevOps for Machine Learning https://www.youtube.com/playlist?list=PLiQS6N-W1p3m9squzZ2cPgGdH5SBhjY6f

MLOps with Azure ML https://github.com/microsoft/MLOpsPython

MLOps v2 https://github.com/Azure/mlops-v2

AI/ML Security

Azure Machine Learning Security https://github.com/caiomsouza/azure-machine-learning-security

Responsible AI

https://fairlearn.org/
https://interpret.ml/
https://www.microsoft.com/en-us/ai/our-approach?activetab=pivot1%3aprimaryr5