From the course: Amazon Web Services Machine Learning Essential Training

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Advanced use of SageMaker

Advanced use of SageMaker - Amazon Web Services (AWS) Tutorial

From the course: Amazon Web Services Machine Learning Essential Training

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Advanced use of SageMaker

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- In addition to what we've seen already around supporting the machine learning life cycle in Sagemaker, there are several scenarios for advanced usage. Now I just want to point out a couple of my favorites here. So, one of them is deploying multiple variants of a model to the same endpoint for A/B testing of different varieties or flavors of a model. It could be trained with different data. It could be set with different hyperparameters. So you can easily do that with Sagemaker. Additionally, you can update the endpoint by providing an updated endpoint configuration to change the machine learning computer instance type or the distribution of traffic among the model variants. You can also log endpoint access with CloudTrail. My personal favorite is using only the needed components of Sagemaker. And to that end, I worked with my college-aged daughter, who is using Sagemaker, specifically the component around hosted Jupyter notebooks, to help her with her bioinformatics research at…

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