Global AI Workshops
  • Welcome
  • Getting started
    • Lab 1 - Get Azure Access
    • Lab 2 - Setup Dev Environment
  • The Azure Function that can see
    • Introduction
    • Lab 1 - Train your model
    • Lab 2 - Create the Function
    • Clean up
  • Cognitive Services
    • Lab 1 - Cognitive Search
    • Lab 2 - Bot Composer
  • Azure machine learning
    • Introduction
    • Lab 1 - AML Workspace Setup
    • Lab 2 - Data
    • Lab 3 - Train your model
    • Lab 4 - Deploy to an ACI
      • Lab 4.2 - Deploy to ACI using the Azure Portal
      • Lab 4.1 - Deploy to ACI using Python
    • Lab 5 - Deploy to Managed Endpoint
    • Clean Up
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  1. Azure machine learning

Introduction

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Last updated 3 years ago

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Train and deploy a PyTorch model using the Azure Machine Learning platform.

In this hands-on lab you are going to build and deploy your own trained vision model to a highly scalable endpoint using Azure Machine Learning.

You start with setting up your cloud workspace and learn how to manage your data and make it reusable. Next you will train a PyTorch model using the transfer learning approach and finally you deploy the model wrapped in an API in a managed endpoint.

At the end of this hands-on lab you have gone through the complete life-cycle of a model, from data to deployment using the Azure Machine Learning platform.

​Title

​Title

Duration:

3 hours

Format:

Hands-on Lab

Pre-Requirements:

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Level:

200-300

Some level of programming & Azure will be helpful

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Azure Access
Dev Environment