课程: Advanced AI Analytics on AWS: Amazon Bedrock, Q, SageMaker Data Wrangler, and QuickSight

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Translating analytics workflows with Q: Python CLI demo

Translating analytics workflows with Q: Python CLI demo

课程: Advanced AI Analytics on AWS: Amazon Bedrock, Q, SageMaker Data Wrangler, and QuickSight

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Translating analytics workflows with Q: Python CLI demo

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- [Instructor] A very common task for a analytics professional, machine learning professional, AI engineer is to deal with data and interact with commands from the command line. And often it can be overwhelming, but one of the things we can do is use generative AI to help us. In this case we use Amazon Q. I'm going to go ahead and open up the cloud shell. Now, the first thing I would do when I am working with this cloud shell is take a look at this thing called Q translate. Let's go ahead and take a look and we'll type in q translate. And what it does is it translates text to a shell. So in this case we can say, list buckets in AWS. So this could be something that would be a very common task for a data engineer, for example. And here we go. Ah, great. So I can actually see exactly how to list a bucket in AWS. Great, I know the syntax. And we can go ahead and we can cancel here. Now the next thing I'm going to show is that oftentimes you also may want to initially build something…

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