Now use Object Tags in the Amazon Machine Learning Console
You now have the ability to add, modify, remove, and list tags on an object through the Amazon Machine Learning (Amazon ML) console. Additionally, when objects are created through the Console wizard, existing tags of the antecedent objects (S3 bucket, Redshift cluster, Data source, ML model) will also be carried over into the new object.
You now have the ability to add, modify, remove, and list tags on an object through the Amazon Machine Learning (Amazon ML) console. Additionally, when objects are created through the Console wizard, existing tags of the antecedent objects (S3 bucket, Redshift cluster, Data source, ML model) will also be carried over into the new object.
Tags are often used to organize resources, such as allocating costs to projects and related budgets while still using AWS offerings from a single account. Using a standardized process for cost allocation through tags can save many administrative hours of your time per month. In addition to cost allocation, tagging can be used for organization and lifecycle management. By example, tags can be used to identify data provenance and model classification, compliance requirements and retention, and change control.
To learn more about tagging through the Amazon Machine Learning console, visit the Amazon ML documentation.