Microsoft DP-100 Exam With Confidence Using Practice Dumps

Scenario: Testing

You must produce multiple partitions of a dataset based on sampling using the Partition and Sample module in Azure Machine Learning Studio.

Box 1: Assign to folds

Use Assign to folds option when you want to divide the dataset into subsets of the data. This option is also useful when you want to create a custom number of folds for cross-validation, or to split rows into several groups.

Not Head: Use Head mode to get only the first n rows. This option is useful if you want to test a pipeline on a small number of rows, and don't need the data to be balanced or sampled in any way.

Not Sampling: The Sampling option supports simple random sampling or stratified random sampling. This is useful if you want to create a smaller representative sample dataset for testing.

Box 2: Partition evenly

Specify the partitioner method: Indicate how you want data to be apportioned to each partition, using these options:

Partition evenly: Use this option to place an equal number of rows in each partition. To specify the number of output partitions, type a whole number in the Specify number of folds to split evenly into text box.

Box 1: Local web service

The Local web service compute target is used for testing/debugging. Use it for limited testing and troubleshooting. Hardware acceleration depends on use of libraries in the local system.

Box 2: Azure Kubernetes Service (AKS)

Azure Kubernetes Service (AKS) is used for Real-time inference.

Recommended for production workloads.

Use it for high-scale production deployments. Provides fast response time and autoscaling of the deployed service