Amazon SageMaker

Amazon SageMaker provides a fully managed cloud platform for users to develop ML models from end to end. Some of the key features of Amazon SageMaker are as follows:

• Data preparation: Amazon SageMaker provides various tools to preprocess and prepare data
• Model training algorithms: SageMaker provides built-in algorithms for supervised learning, unsupervised learning, and reinforcement learning
• Model deployment: After the ML model is trained and validated, SageMaker provides tools for model deployment, either as a batch transform job or a real-time endpoint
• Scalability: SageMaker is a fully managed service, which means that AWS takes care of all the infrastructure and scaling, so the data scientists can focus on building better models rather than worrying about infrastructure
• Integration: SageMaker integrates with other AWS services, such as S3, AWS Glue, and AWS Lambda, so data scientists can easily access and use datasets stored in AWS

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