Azure Machine Learning & MLOps : Beginner to Advance
You are looking for a comprehensive, engaging, and fun course for mastering Azure Machine learning ( up to even advanced industry-required
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What you'll learn
- How to use Azure Machine Learning from Development to Production
- How to Use Azure DevOps for Continuous Integration, continuous deployment on Machine Learning
- How to automate End 2 End machine Learning Solution on Azure
- How to Deploy Machine learning Models on Azure (Azure Container Instances, Azure Kubernetese Services, managed endpoints)
- Run an end-to-end CI/CD MLOps pipeline using Azure DevOps & Azure Machine learning
- Bests practices and highly demanded capabilities of machine learning on Azure Cloud
A course instructed by me and my digital twin if:
You are looking for a comprehensive, engaging, and fun course for mastering Azure Machine learning ( up to even advanced industry-required topics) plus fully hands-on end-to-end implantation of MLOps ( DevOps for Machine learning on Azure). If yes, then this is the right and very unique course for you!
Machine Learning Operations (MLOps) is a rapidly growing culture nad highly demanded in the industry with a set of principles, and guidelines defined in the machine learning world to deploy a machine learning model into production.
Azure Machine Learning is a cloud service for accelerating and managing the machine learning project lifecycle. Machine learning professionals, data scientists, and engineers can use it in their day-to-day workflows: Train and deploy models, and manage MLOps.
You can create a model in Azure Machine Learning or use a model built from an open-source platform, such as Pytorch, TensorFlow, or scikit-learn. MLOps tools help you monitor, retrain, and redeploy models.