Episode

FastTrack for Azure Season 2 Ep03: Azure ML Developer Experience

with Meer Alam, Varma Gadhiraju, Jameel Ahmed

Learn Live

In this session you will get a solid understanding of the overall on the concept of Training models with Azure Machine Learning (AzureML) CLI, SDK, and REST API by walking through step-by-step examples, leading up to ML model lifecycle management leveraging Azure ML Python SDK V2 so we can help accelerate your AI journey in the cloud. We will review how we work with ML models in Azure ML Python SDK V2 and then demonstrates how we leverage Azure ML Python SDK V2 to work with ML models in local environment or with ML Studio.

Learning objectives

  • Azure ML Components
  • How to organize ML solution
  • Enterprise Security
  • Training
  • Deployment

Chapters

  • 00:00 - Welcome
  • 01:53 - Introduction
  • 03:16 - Learning Objectives
  • 16:02 - Azure Machine Learning Workspace Overview
  • 01:06:35 - Azure ML Studio, Notebook, Azure ML Python SDK V2 and CLI V2 way of Training and deploying models, through VS code, connecting remotely to Compute Instance, demo.
  • 01:28:14 - Tips and Tricks: Attaching to the VS code, debugging Functionality, Azure ML HTTP Inference Server
  • 01:29:16 - Closure

Connect

Intermediate
AI Engineer
Data Scientist
Data Analyst
Azure Machine Learning