What is Azure Machine Learning service and how data scientists use it
An easier way for data scientists to build reproducible experiments with machine learning pipelines and communicate operational dependencies to their engineering counterparts as part of a new MLOps approach you deploy to the Cloud and the Edge at scale. Chris Lauren the Principal Program Manager for the Azure Machine Learning Platform goes over the new Azure Machine Learning service. Chris shows you what capabilities data scientists can get across the machine learning lifecycle within a familiar notebook experience. And you'll see how you can use the newly introduced Automated Machine Learning capabilities in Azure ML to build machine learning models in a fraction of the time.

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Getting Started with Azure ML Pipelines

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MLOps Explained - What It Is, Why You Need It and How It Works

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Azure Machine Learning Studio

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MLOps explained | Machine Learning Essentials

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Azure AI Foundry Overview

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What is Azure Synapse Analytics? Generally Available Today.

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Azure Kubernetes Services (AKS) Overview

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Azure Machine Learning Tutorial | Azure Tutorial | Azure Training | Edureka Rewind

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Introducing Azure AI Foundry - Everything you need for AI development

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Basic first project! Azure Machine Learning Easy Getting Starting For Fun and Profit!

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Introducing the new Azure Copilot for the new era of Intelligent Agents | BRK145

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Azure AI Fundamentals Certification (AI-900) - Full Course to PASS the Exam

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Terraform explained in 15 mins | Terraform Tutorial for Beginners

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Introducing the modern data warehouse solution pattern with Azure SQL Data Warehouse

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Microsoft Azure Data Scientist Certification (DP-100): Train machine learning models at scale

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Fine-tune and deploy foundation models with Azure Machine Learning

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Get Started with Azure Machine Learning
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Azure Synapse | Azure Synapse Analytics [Full Course] ☁️

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Low-code machine learning in Azure | Machine Learning Essentials

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