Learn how to use the Split Data module in the Azure Machine Learning designer to create a training dataset and validation dataset from an existing dataset for the AI-900: Microsoft Azure AI Fundamentals certification exam.
Table of Contents
Question
You need to create a training dataset and validation dataset from an existing dataset. Which module in the Azure Machine Learning designer should you use?
A. Select Columns in Dataset
B. Add Rows
C. Split Data
D. Join Data
Answer
C. Split Data
Explanation
A common way of evaluating a model is to divide the data into a training and test set by using Split Data, and then validate the model on the training data.
Use the Split Data module to divide a dataset into two distinct sets.
The studio currently supports training/validation data splits
The correct answer is C. Split Data. This module allows you to split a dataset into two subsets based on a specified percentage or expression. You can use one subset for training and the other for validation. The other modules do not perform this function.
A. Select Columns in Dataset: This module allows you to select specific columns from a dataset and create a new dataset with only those columns. B. Add Rows: This module allows you to append rows from one dataset to another dataset and create a new dataset with the combined rows. D. Join Data: This module allows you to join two datasets based on a common key and create a new dataset with the joined columns.
Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.
