CI pipeline & Azure ML Online Endpoints: Deploy ML Models to Production

Learn the practical steps to deploy machine learning models using Azure ML Online Endpoints. This guide bridges the gap between model development and production deployment with ready-to-use scripts and configurations. Built for data scientists and ML engineers who need reliable, scalable model serving solutions.
🎯 Key Features:
Automated CLI deployment scripts
Production-ready YAML configurations
Traffic management and A/B testing
Real-time inference setup
Performance monitoring
⚡ What You'll Learn:
Setting up Azure ML Online Endpoints from scratch
Automating deployments with Azure DevOps
Implementing real-time inference
Managing traffic and A/B testing
Monitoring model performance
⚡ Built for:
ML Engineers
Data Scientists
DevOps Engineers
Cloud Architects
🔍 Perfect for: ML Engineers, Data Scientists, DevOps Engineers, and Cloud Architects
More Azure Learning Resources:
Code: [github.com/Dee...]
Azure Machine Learning (DP-100) Playlist: [ • Azure ml ]
Azure DevOps Playlist: [ • azure devops ]
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Medium: [ / deepp.knowledge ]
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