From the course: Learning Amazon SageMaker

How does Amazon SageMaker work?

From the course: Learning Amazon SageMaker

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How does Amazon SageMaker work?

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- [Instructor] How does SageMaker work? Amazon SageMaker is not one software tool, but rather a collection of tools and services. All of these tools and services allow the training and deployment of machine learning models. Similar to a menu at a restaurant, you can choose and select different items, combinations of items based on your needs. You're also allowed to use other services and tools based on the problem that you're looking to solve. In the simplest of terms, the tools that are provided allowing the training and deployment of the model. Again, with the weather example that I spoke about before, perhaps you have a data set based on the weather for the last few days and you would like to predict if it would rain tomorrow. You can use that data set, import it into Amazon SageMaker, using their libraries, using your own code, and you can train and deploy a model. Amazon SageMaker provides an analytical environment as a service to parse the previous weather data. It also provides tools to manipulate this data and train a model. You can use your own tools to build the model if you wish. And those tools would usually be comprised of different Python modules or Python code that you've written. The platform provides tools to host the model as an API, but you can also set up your own API if you wish. You can even set up your own API in other cloud services. There are many ways to customize this process. And the approach might seem daunting, but once you run through a basic pattern, the opportunities for creation are pretty much endless.

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