# Managing Amazon Rekognition Custom Labels resources
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This section gives you an overview of the Amazon Rekognition Custom Labels resources you use to train and manage a model. Also included is overview information for using the AWS SDK to train and use a model. 

 Amazon Rekognition Custom Labels relies on three different resources to detect your custom labels: projects, datasets, and models. 
+ Projects - Used to group other resouces like datasets, model versions, and model evaluations together. 
+ Datasets - Defines images and associated metadata for use in training and testing models. You can create a dataset by using a SageMaker AI format manifest file or by copying an existing Amazon Rekognition Custom Labels dataset.
+ Models - The mathematical model that actually predicts the presence of objects, scenes, and concepts in images by identifying patterns in images used to train the model.



**Topics**
+ [Managing an Amazon Rekognition Custom Labels project](managing-project.md)
+ [Managing datasets](managing-dataset.md)
+ [Managing an Amazon Rekognition Custom Labels model](managing-model.md)