MLOps Pipeline on Azure Kubernetes
Machine Learning
AI Specialist
Project Overview
Engineered end-to-end ML pipelines with Azure ML Workspace, Kubernetes, and CI/CD, improving deployment speed and security.
Detailed Description
Engineered a complete MLOps pipeline on Azure, leveraging Azure ML Workspace for model training and management, and Azure Kubernetes Service (AKS) for scalable deployment.
The CI/CD pipeline automated the entire process from code commit to model deployment, significantly improving deployment frequency, reliability, and security.
Key Technologies
Azure ML
Kubernetes
Python
CI/CD
Challenges & Solutions
Automating the entire machine learning lifecycle, from data preprocessing to model deployment and monitoring, required building a robust and reproducible MLOps pipeline from scratch.