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Build machine learning models with Amazon SageMaker optimal for your use case

March 22, 2022

Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning (ML) models by bringing together a broad set of capabilities purpose-built for ML. Based on your specific use case, in Amazon SageMaker you can pick from over 15 algorithms that are built-in and optimized for Amazon SageMaker or you can build models using popular deep learning or machine learning frameworks managed by AWS or bring your own container. You can also build models using over 150 pre-built models from popular model zoos available with just a few clicks. In this session, we provide an overview on the various ways you can build models with Amazon SageMaker efficiently, focusing on a range of SageMaker capabilities including; in-built algorithms, framework containers, Amazon SageMaker Autopilot and Amazon SageMaker JumpStart.
Speaker: Romina Sharifpour, AI/ML Specialist Solutions Architect, AWS

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Data preparation Using Amazon SageMaker and AWS Glue DataBrew
Data preparation Using Amazon SageMaker and AWS Glue DataBrew

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Train ML models quickly and cost-effectively with Amazon SageMaker
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