Learn Live - Azure ML Operations

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Full series information: https://aka.ms/learnlive-202302FT More info here: https://aka.ms/learnlive-202302FT-Ep4 Follow on Microsoft Learn: - Session documentation: https://aka.ms/learnlive-20230307FT This live session will introduce the concepts of MLOps, discuss how organizations can adopt MLOps practices, and develop a machine learning lifecycle from a technical perspective. --------------------- Learning objectives - Operationalization of an end-to-end ML solution through Azure ML and DevOps practices --------------------- Chapters -------- 00:00 - Welcome 02:08 - Introduction 02:47 - Learning Objectives 06:51 - Over of Machine Learning Operations (MLOps) 09:16 - Walkthrough the Mindmap of MLOps 16:04 - Data Preparation for your ML Model 20:19 - Azure ML Computes for your Model training 22:55 - Model Training Environment 24:45 - Azure Databricks has similar components like Data Assets, Compute, Environment like we have in Azure ML 28:31 - Authoring your models - Azure ML Studio Designer, Automated ML and Notbooks 32:00 - Azure ML Jobs 35:05 - Use Components to create Azure ML Pipeline 40:54 - Deploying your models to an Endpoint - Model Development Cycle Completed in Azure ML Studio 44:04 - How Does Registry help in MLOps? 47:05 - Leverage Azure ML Python SDK V2 for your Model Training 1:05:46 - Demo - ML pipelines with Python SDK V2 1:26:24 - DevOps for ML Solution - Walkthrough with Azure DevOps and GitHub Action to automate end-to-end operational

Published 2023-03-07 · Watch on YouTube ↗
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