From the course: Microsoft Azure Data Scientist Associate (DP-100) Cert Prep
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Test a real-time deployed service - Azure Tutorial
From the course: Microsoft Azure Data Scientist Associate (DP-100) Cert Prep
Test a real-time deployed service
- [Instructor] Let's take a look at how we can go from data itself stored in the DBFS and actually take that data and go to AutoML and really create a high level end-to-end experience. So as long as something is inside of the Databricks file system, and in this case we have two tables here, we have the diamonds table and the people table, we can actually do things with it. And in particular, if I go to the diamonds table here, and let's go to take a look at this. One of the nice things about the data exploration tool here is that it'll give you the schema, it'll show you a little bit of a sample for the data, so you can actually take a look at the features that you would want to use potentially in an AutoML experiment. So now that I know that there are some features here, like carat, cut, color, you know, things like that, that could be one thing I do. Likewise, if I go to the people right here, and I go into this database, you can see that there's a bunch of columns here that I can…
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Configure compute for a batch deployment2m 11s
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Deploy a model to a batch endpoint4m 2s
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Test a real-time deployed service4m 23s
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Apply machine learning operations (MLOps) practices4m 32s
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Trigger an Azure Machine Learning pipeline, including from Azure DevOps or GitHub2m 36s
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Conclusion1m 6s
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