- Our last task that we are going to do … with Azure's Machine Learning … is to create a model from a data file … to protect the budget vote based on other votes … by the members of the 1984 House of Representatives. … For this, we are going to use Azure Machine Learning Studio … back in the Azure Portal. … To get started, I'm going to click on Create a Resource. … And we're going to search for Azure Machine Learning Studio. … Now we can get rid of the word Azure in the front. … So we'll find it. … And we want the Workspace, … so I'll click on the Workspace version. … And then press create. … All right. … And we're going to name this … LinkedInMachineLearningWorkspace. … And the description, we're going to leave it … Visual Studio Premium. … And the resource group, … we're going to choose the one we created earlier. … LinkedIn Training. … And on the pricing tier, we'll click on that. … And select our DEVTEST Standard. … This is the free pricing tier. … We get to create on of those. … So we'll select that. …
Author
Kevin Ford
Released
3/21/2019- Defining machine learning
- Training a machine learning model
- Comparing machine learning frameworks
- Using IBM Watson for mobile machine learning
- Using Azure Machine Learning for speech and image recognition
- Training Core ML models
- Comparing client-side and server-side models
Skill Level Beginner
Duration
Views
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Introduction
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What you should know1m 1s
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Using the exercise files2m 36s
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1. Introduction to Machine Learning
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What is machine learning?2m 27s
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Required concepts2m 53s
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Training a model2m 14s
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ML frameworks2m 56s
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2. Server Models: IBM Watson
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Overview of Watson2m 1s
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Visual Recognition: Set up1m 41s
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Create a custom model3m 37s
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Install client SDK package3m 45s
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Run the client app3m 27s
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3. Server Models: Azure Machine Learning
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Custom Vision: Set up4m 25s
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Install client SDK package2m 27s
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Client tie to LUIS5m 16s
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Run the clent app2m 12s
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4. Client Models: Core ML
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Core ML overview2m 10s
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Run the client app1m 45s
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5. Understanding the Offerings
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Conclusion
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Next steps1m 40s
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Video: Machine Learning Studio: Set up