ML using Amazon SageMaker, along with use cases
One of the biggest barriers to ML adoption has been that not everyone in the organization understands how the ML process works or has the skill sets to build an end-to-end ML platform. Amazon SageMaker is a comprehensive ML service that helps different personas easily use the platform to build, train, and deploy ML models for any use case. Data scientists want to quickly prepare the data to train and build ML models. ML engineers want to quickly deploy and manage these models at scale. Business analysts want to make ML predictions without having to learn ML technologies. This is where Amazon SageMaker as an ML platform helps. It’s a collection of tools that make every step of the ML process easier, faster, and cheaper to implement for different personas in the organization. The following diagram depicts this aspect of SageMaker:
Figure 10.6 – Amazon SageMaker user personas
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