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Amazon Sage Maker

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You can create, train, and deploy ML models for any use case with Amazon SageMaker, a fully managed service. In order to encourage more individuals to create using ML, it offers completely managed infrastructure, products, and processes. Benefits Data scientists and analysts have access to a variety of tools. Capacity to retrieve, categorize, and handle massive volumes of data for ML purposes. Thanks to an enhanced infrastructure, training time was cut in half, from hours to minutes. Tools designed specifically for teams can boost output by a factor of up to 10. Enhanced openness and auditability through the implementation of standardized and automated MLOps procedures and governance across all enterprises. Business analysts can use SageMaker Canvas, a visual interface, to develop ML predictions for use cases. With SageMaker Studio, data scientists can clean up their data and construct, train, and release models. If ML developers use SageMaker MLOps, they can manage and deploy models on a massive scale. You can use Amazon SageMaker with any of the top machine learning (ML) frameworks, toolkits, or languages. Amazon has spent the last 20 years perfecting ML applications for use in intelligent shopping, voice-assisted gadgets, robotics, product suggestions, and personalization.

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