AWS sagemaker documentation change
Summary
Updated workshop page URLs by adding '/zzz-legacy' path segment in multiple dataset entries
Security assessment
The changes only modify workshop URL paths to include 'zzz-legacy' directory without any security context. This appears to be documentation restructuring for workshop organization rather than addressing security vulnerabilities or describing security features.
Diff
diff --git a/sagemaker/latest/dg/canvas-sample-datasets.md b/sagemaker/latest/dg/canvas-sample-datasets.md index 7cc8ae949..2b5f6d17a 100644 --- a//sagemaker/latest/dg/canvas-sample-datasets.md +++ b//sagemaker/latest/dg/canvas-sample-datasets.md @@ -11 +11 @@ The following datasets are the samples that SageMaker Canvas provides by default - * **canvas-sample-diabetic-readmission.csv:** This dataset contains historical data including over fifteen features with patient and hospital outcomes. You can use this dataset to predict whether high-risk diabetic patients are likely to get readmitted to the hospital within 30 days of discharge, after 30 days, or not at all. Use the **redadmitted** column as the target column, and use the 3+ category prediction model type with this dataset. To learn more about how to build a model with this dataset, see the [SageMaker Canvas workshop page](https://catalog.us-east-1.prod.workshops.aws/workshops/80ba0ea5-7cf9-4b8c-9d3f-1cd988b6c071/en-US/1-use-cases/5-hcls). This dataset was obtained from the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/diabetes+130-us+hospitals+for+years+1999-2008). + * **canvas-sample-diabetic-readmission.csv:** This dataset contains historical data including over fifteen features with patient and hospital outcomes. You can use this dataset to predict whether high-risk diabetic patients are likely to get readmitted to the hospital within 30 days of discharge, after 30 days, or not at all. Use the **redadmitted** column as the target column, and use the 3+ category prediction model type with this dataset. To learn more about how to build a model with this dataset, see the [SageMaker Canvas workshop page](https://catalog.us-east-1.prod.workshops.aws/workshops/80ba0ea5-7cf9-4b8c-9d3f-1cd988b6c071/en-US/zzz-legacy/1-use-cases/5-hcls). This dataset was obtained from the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/diabetes+130-us+hospitals+for+years+1999-2008). @@ -13 +13 @@ The following datasets are the samples that SageMaker Canvas provides by default - * **canvas-sample-housing.csv:** This dataset contains data on the characteristics tied to a given housing price. You can use this dataset to predict housing prices. Use the **median_house_value** column as the target column, and use the numeric prediction model type with this dataset. To learn more about building a model with this dataset, see the [SageMaker Canvas workshop page](https://catalog.us-east-1.prod.workshops.aws/workshops/80ba0ea5-7cf9-4b8c-9d3f-1cd988b6c071/en-US/1-use-cases/2-real-estate). This is the California housing dataset obtained from the [StatLib repository](https://www.dcc.fc.up.pt/~ltorgo/Regression/cal_housing.html). + * **canvas-sample-housing.csv:** This dataset contains data on the characteristics tied to a given housing price. You can use this dataset to predict housing prices. Use the **median_house_value** column as the target column, and use the numeric prediction model type with this dataset. To learn more about building a model with this dataset, see the [SageMaker Canvas workshop page](https://catalog.us-east-1.prod.workshops.aws/workshops/80ba0ea5-7cf9-4b8c-9d3f-1cd988b6c071/en-US/zzz-legacy/1-use-cases/2-real-estate). This is the California housing dataset obtained from the [StatLib repository](https://www.dcc.fc.up.pt/~ltorgo/Regression/cal_housing.html). @@ -15 +15 @@ The following datasets are the samples that SageMaker Canvas provides by default - * **canvas-sample-loans.csv:** This dataset contains complete loan data for all loans issued from 2007–2011, including the current loan status and latest payment information. You can use this dataset to predict whether a customer will repay a loan. Use the **loan_status** column as the target column, and use the 3+ category prediction model type with this dataset. To learn more about how to build a model with this dataset, see the [SageMaker Canvas workshop page](https://catalog.us-east-1.prod.workshops.aws/workshops/80ba0ea5-7cf9-4b8c-9d3f-1cd988b6c071/en-US/1-use-cases/4-finserv). This data uses the LendingClub data obtained from [Kaggle](https://www.kaggle.com/datasets/wordsforthewise/lending-club). + * **canvas-sample-loans.csv:** This dataset contains complete loan data for all loans issued from 2007–2011, including the current loan status and latest payment information. You can use this dataset to predict whether a customer will repay a loan. Use the **loan_status** column as the target column, and use the 3+ category prediction model type with this dataset. To learn more about how to build a model with this dataset, see the [SageMaker Canvas workshop page](https://catalog.us-east-1.prod.workshops.aws/workshops/80ba0ea5-7cf9-4b8c-9d3f-1cd988b6c071/en-US/zzz-legacy/1-use-cases/4-finserv). This data uses the LendingClub data obtained from [Kaggle](https://www.kaggle.com/datasets/wordsforthewise/lending-club). @@ -17 +17 @@ The following datasets are the samples that SageMaker Canvas provides by default - * **canvas-sample-maintenance.csv:** This dataset contains data on the characteristics tied to a given maintenance failure type. You can use this dataset to predict which failure will occur in the future. Use the **Failure Type** column as the target column, and use the 3+ category prediction model type with this dataset. To learn more about how to build a model with this dataset, see the [SageMaker Canvas workshop page](https://catalog.us-east-1.prod.workshops.aws/workshops/80ba0ea5-7cf9-4b8c-9d3f-1cd988b6c071/en-US/1-use-cases/6-manufacturing). This dataset was obtained from the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/AI4I+2020+Predictive+Maintenance+Dataset). + * **canvas-sample-maintenance.csv:** This dataset contains data on the characteristics tied to a given maintenance failure type. You can use this dataset to predict which failure will occur in the future. Use the **Failure Type** column as the target column, and use the 3+ category prediction model type with this dataset. To learn more about how to build a model with this dataset, see the [SageMaker Canvas workshop page](https://catalog.us-east-1.prod.workshops.aws/workshops/80ba0ea5-7cf9-4b8c-9d3f-1cd988b6c071/en-US/zzz-legacy/1-use-cases/6-manufacturing). This dataset was obtained from the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/AI4I+2020+Predictive+Maintenance+Dataset). @@ -19 +19 @@ The following datasets are the samples that SageMaker Canvas provides by default - * **canvas-sample-shipping-logs.csv:** This dataset contains complete shipping data for all products delivered, including estimated time shipping priority, carrier, and origin. You can use this dataset to predict the estimated time of arrival of the shipment in number of days. Use the **ActualShippingDays** column as the target column, and use the numeric prediction model type with this dataset. To learn more about how to build a model with this data, see the [SageMaker Canvas workshop page](https://catalog.us-east-1.prod.workshops.aws/workshops/80ba0ea5-7cf9-4b8c-9d3f-1cd988b6c071/en-US/1-use-cases/7-supply-chain). This is a synthetic dataset created by Amazon. + * **canvas-sample-shipping-logs.csv:** This dataset contains complete shipping data for all products delivered, including estimated time shipping priority, carrier, and origin. You can use this dataset to predict the estimated time of arrival of the shipment in number of days. Use the **ActualShippingDays** column as the target column, and use the numeric prediction model type with this dataset. To learn more about how to build a model with this data, see the [SageMaker Canvas workshop page](https://catalog.us-east-1.prod.workshops.aws/workshops/80ba0ea5-7cf9-4b8c-9d3f-1cd988b6c071/en-US/zzz-legacy/1-use-cases/7-supply-chain). This is a synthetic dataset created by Amazon. @@ -21 +21 @@ The following datasets are the samples that SageMaker Canvas provides by default - * **canvas-sample-sales-forecasting.csv:** This dataset contains historical time series sales data for retail stores. You can use this dataset to forecast sales for a particular retail store. Use the **sales** column as the target column, and use the time series forecasting model type with this dataset. To learn more about how to build a model with this dataset, see the [SageMaker Canvas workshop page](https://catalog.us-east-1.prod.workshops.aws/workshops/80ba0ea5-7cf9-4b8c-9d3f-1cd988b6c071/en-US/1-use-cases/3-retail). This is a synthetic dataset created by Amazon. + * **canvas-sample-sales-forecasting.csv:** This dataset contains historical time series sales data for retail stores. You can use this dataset to forecast sales for a particular retail store. Use the **sales** column as the target column, and use the time series forecasting model type with this dataset. To learn more about how to build a model with this dataset, see the [SageMaker Canvas workshop page](https://catalog.us-east-1.prod.workshops.aws/workshops/80ba0ea5-7cf9-4b8c-9d3f-1cd988b6c071/en-US/zzz-legacy/1-use-cases/3-retail). This is a synthetic dataset created by Amazon.