Remove 2012 Remove Clustering Remove Data Pipeline
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Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

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AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, ML, and application development. Here we use RedshiftDatasetDefinition to retrieve the dataset from the Redshift cluster. We attached the IAM role to the Redshift cluster that we created earlier.

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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

Learning means identifying and capturing historical patterns from the data, and inference means mapping a current value to the historical pattern. The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. Work by Hinton et al.

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Connect, share, and query where your data sits using Amazon SageMaker Unified Studio

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To establish trust between the data producers and data consumers, SageMaker Catalog also integrates the data quality metrics and data lineage events to track and drive transparency in data pipelines. Notice the subscribed asset is shared under the folder project.

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