Azure Machine Learning Workshop

Target Audience

Anyone who wants a comprehensive understanding of Azure ML.

Key Goals

1. Understand the product E2E
2. Get confident with the basis of the Azure ML Python SDK

Agenda

Workspace Concepts

1. Set up your workspace and compute
2. Register a dataset
3. Run AutoML from the UI
4. Azure ML Designer
5. Compute Instance - Clone Git Repo

Training and Logging

Azure ML Training & HyperDrive

1. Training of a classification model and interactive logging on Azure ML
2. Remote training via Azure ML Cluster

Azure ML Interpretability

1. Setup
2. Explain binary classification model predictions locally

Training Using AutoML

1. AutoML on Local Compute
2. AutoML on Remote Compute

Deploy the Model on an Azure Web Services

1. Deploying a web service to Azure Container Instance (ACI) or Azure Kubernetes Services (AKS)