September 2019
Intermediate to advanced
528 pages
14h 24m
English
Content preview from Machine Learning in the AWS Cloud
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Chapter 16Amazon SageMaker
WHAT'S IN THIS CHAPTER
- Introduction to the Amazon SageMaker service
- Create an Amazon SageMaker notebook instance
- Train a Scikit-learn model locally on the notebook instance
- Train a Scikit-learn model on a dedicated instance
- Use Amazon SageMaker's built-in algorithms
- Create prediction endpoints
Amazon SageMaker is a fully managed web service that provides the ability to explore data, engineer features, and train machine learning models on AWS cloud infrastructure using Python code. Once you have trained your model, you can deploy the model to a cluster of dedicated compute instances and use the deployed model to get predictions one item at a time or create batch predictions on entire datasets.
Amazon SageMaker provides ...
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