From the course: Amazon Web Services Machine Learning Essential Training
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Deploy and host model with SageMaker model - Amazon Web Services (AWS) Tutorial
From the course: Amazon Web Services Machine Learning Essential Training
Deploy and host model with SageMaker model
- [Instructor] So I'm going to scroll down, and this tells us here we can deploy the model we just trained behind a real time hosted end point, and again, these examples are not optimized for production. They're just to get us started, so really don't take this as the performance of this service. Hence why Amazon's telling you this here. So we're going to go ahead and call deploy, and pass in an instance count of one, and there's our instance type, and then we'll click on the cell and press Shift + Return to execute that, and what's really kind of amazing about this is how much of the infrastructure Amazon has abstracted away. Now, while this is running, just to be complete, I'll show you that they actually do have, in their GUI console interface, the capability to click and do this. So let me just go back over here and you can see that we have instances and we have jobs, and of course, that's the job that we just ran. So that's model training, if you remember. If we click in here we…
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Contents
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Understanding ML platforms3m 53s
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Understanding and using AWS Machine Learning9m 15s
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Understanding SageMaker3m 54s
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Create Jupyter notebooks with SageMaker6m 12s
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Get data with SageMaker notebook6m 25s
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Train model with SageMaker job3m 6s
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Deploy and host model with SageMaker model2m 31s
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Use model from SageMaker endpoint4m 7s
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Selecting algorithm for model training5m 36s
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Advanced use of SageMaker2m 37s
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