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AI-900: Scaling Numeric Features in Azure ML Normalize Data Module Explained

Learn how to standardize numeric features effectively in Azure ML using the Normalize Data module, ensuring consistent scales for improved model training and accuracy.

Table of Contents

Question

You need to bring numeric features to the common scale in your dataset.

What Azure ML Designer module will you use for this purpose?

A. Select Columns in Dataset
B. Clean Missing Data
C. Normalize Data
D. Split Data
E. Clip Values

Answer

C. Normalize Data

Explanation

You’d utilize the “Normalize Data” module in Azure ML Designer to bring numeric features to a common scale. This module scales the values within a specified range, like [0,1] or [-1,1], ensuring all features contribute evenly to model training.

You need to normalize your numeric features. The process of normalization brings numeric features to a common scale.

Azure ML Designer provides the Normalize Data module for this purpose.

Data before the Normalize data module.

And data after Normalize Data module.

Option A is incorrect. “Select Columns in Dataset” module helps select or exclude columns from the model training dataset.
Option B is incorrect. “Clean Missing Data” module takes care of missing data in a dataset.
Option D is incorrect. “Split Data” module divides data into training and testing datasets.
Option E is incorrect. “Clip Values” module detects outliers and clips or replaces their values.

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.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump

Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook

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