12:40 - 03:00
Introduction Azure Machine Learning techniques
- Jupytyer Notebook
- Azure ML -python SDK
- Azure ML Studio
- Hands on Lab
- Create a workspace.
- Create a cloud-based compute instance to use for your development environment.
- Create a cloud-based compute cluster to use for training your model.
- Connect to your Azure ML workspace
- Create Azure ML data assets
- Create reusable Azure ML components
- Create, validate and run Azure ML pipelines
- Deploy the newly-trained model as an endpoint
- Call the Azure ML endpoint for inferencing
Basic to intermediate Machine learning Knowledge
Must be aware of Azure Cloud concept & generic storage, workspace, resources concept