AWS clean-rooms documentation change
Summary
Added 'in AWS Clean Rooms ML' qualifiers to documentation links and maintained consistent product naming
Security assessment
Changes focus on documentation consistency and product branding rather than security aspects. No new security controls or vulnerabilities addressed.
Diff
diff --git a/clean-rooms/latest/userguide/machine-learning.md b/clean-rooms/latest/userguide/machine-learning.md index 55e2ccfdc..3d67d3bd4 100644 --- a//clean-rooms/latest/userguide/machine-learning.md +++ b//clean-rooms/latest/userguide/machine-learning.md @@ -68 +68 @@ At the highest level, here are the steps that must be completed to perform custo - 1. The collaboration creator creates a collaboration and assigns each member the proper member abilities and payment configuration. The collaboration creator must assign the member ability to either receive model outputs or receive inference results to the appropriate member in this step because it can't be updated after the collaboration is created. For more information, see [Creating the collaboration](./create-custom-ml-collaboration.html). + 1. The collaboration creator creates a collaboration and assigns each member the proper member abilities and payment configuration. The collaboration creator must assign the member ability to either receive model outputs or receive inference results to the appropriate member in this step because it can't be updated after the collaboration is created. For more information, see [Creating and joining the collaboration in AWS Clean Rooms ML](./create-custom-ml-collaboration.html). @@ -70 +70 @@ At the highest level, here are the steps that must be completed to perform custo - 2. The model provider configures and associates their containerized ML model to the collaboration and ensures privacy constraints are set for exported data. For more information, see [Configuring a model algorithm](./configure-model-algorithm.html). + 2. The model provider configures and associates their containerized ML model to the collaboration and ensures privacy constraints are set for exported data. For more information, see [Configuring a model algorithm in AWS Clean Rooms ML](./configure-model-algorithm.html). @@ -72 +72 @@ At the highest level, here are the steps that must be completed to perform custo - 3. The data providers contribute their data to the collaboration and ensure their privacy needs are specified. Data providers must allow the model to access their data. For more information, see [Contributing training data](./custom-model-training-data.html) and [Associating the configured model algorithm](./associate-model-algorithm.html). + 3. The data providers contribute their data to the collaboration and ensure their privacy needs are specified. Data providers must allow the model to access their data. For more information, see [Contributing training data in AWS Clean Rooms ML](./custom-model-training-data.html) and [Associating the configured model algorithm in AWS Clean Rooms ML](./associate-model-algorithm.html). @@ -78 +78 @@ At the highest level, here are the steps that must be completed to perform custo - 6. A collaboration member invokes model training using the ML input channel and the configured model algorithm. For more information, see [Creating a trained model](./create-trained-model.html). + 6. A collaboration member invokes model training using the ML input channel and the configured model algorithm. For more information, see [Creating a trained model in AWS Clean Rooms ML](./create-trained-model.html). @@ -80 +80 @@ At the highest level, here are the steps that must be completed to perform custo - 7. (Optional) The model trainer invokes the model export job and the model artifacts are sent to the model results receiver. Only members with a valid ML configuration and the member ability to receive model output can receive model artifacts. For more information, see [Exporting model artifacts](./export-model-artifacts.html). + 7. (Optional) The model trainer invokes the model export job and the model artifacts are sent to the model results receiver. Only members with a valid ML configuration and the member ability to receive model output can receive model artifacts. For more information, see [Exporting model artifacts from AWS Clean Rooms ML](./export-model-artifacts.html).