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· 3 min read
Beatriz Stollnitz

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🗓️ Day 5 of #30DaysOfAzureAI

Learn key Azure ML Concepts with this primer

Yesterday we talked about using Copilot to build an intelligent Receipt processing app. Today we'll explore Azure Machine Learning.

🎯 What we'll cover

  • Why use Azure ML
  • The main resources used to train and deploy models in Azure ML
  • The four different ways of creating those resources

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📚 References

🚌 Introduction to Azure ML

Read today's article to understand the benefits of using cloud computing for machine learning projects, and to get an overview of Microsoft's Azure ML platform. Azure ML enables you to train and deploy machine learning models in the cloud, by creating a variety of resources that help tailor the workflow to your needs. Today's article provides an overview of each of those resources, and explains the four different ways of creating them.

The goal for today is for you to get a foundational understanding of Azure ML concepts, so that you'll be able to follow code samples later in the AI April month.

👓 View today's article

Today's article.

🙋🏾‍♂️ Questions?

You can ask questions about this post on GitHub Discussions

📍 30 days roadmap

What's next? View the #30DaysOfAzureAI Roadmap

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