APPLICATION OF SUPERVISED LEARNING
MACHINE LEARNING PIPELINE
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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SageMaker notebook instances
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SageMaker training jobs
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SageMaker hyperaparameter tuning
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SageMaker endpoints
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Detailed explanation-1: -Machine learning (ML) can be extremely useful in this regard because it helps data scientists build those algorithms.
Detailed explanation-2: -SageMaker Ground Truth is a data labeling service that makes it easy to label data and gives you the option to use human annotators through Amazon Mechanical Turk, third-party vendors, or your own private workforce.
Detailed explanation-3: -With SageMaker Clarify, you can identify potential bias during data preparation without having to write your own code as part of Amazon SageMaker Data Wrangler. You specify input features, such as gender or age, and SageMaker Clarify runs an analysis job to detect potential bias in those features.
Detailed explanation-4: -Q: What is Amazon SageMaker Canvas? Amazon SageMaker Canvas is a visual drag-and-drop service that allows business analysts to build ML models and generate accurate predictions without writing any code or requiring ML expertise.