To complete the sentence, select the appropriate option in the answer area.

Correct Answer:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/create-features

Comment: *

Name: *

Email: *

Verification: *

To complete the sentence, select the appropriate option in the answer area.

Correct Answer:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-module-reference/linear-regression
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/machine-learning-initialize-model-clustering Regression is a form of machine learning that is used to predict a numeric label based on an item's features.
https://docs.microsoft.com/en-us/learn/modules/create-regression-model-azure-machine-learning-designer/introduction

Comment: *

Name: *

Email: *

Verification: *

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation:
Box 1: Yes
In machine learning, if you have labeled data, that means your data is marked up, or annotated, to show the target, which is the answer you want your machine learning model to predict.
In general, data labeling can refer to tasks that include data tagging, annotation, classification, moderation, transcription, or processing.
Box 2: No
Box 3: No
Accuracy is simply the proportion of correctly classified instances. It is usually the first metric you look at when evaluating a classifier. However, when the test data is unbalanced (where most of the instances belong to one of the classes), or you are more interested in the performance on either one of the classes, accuracy doesn't really capture the effectiveness of a classifier.
Reference:
https://www.cloudfactory.com/data-labeling-guide
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance

Comment: *

Name: *

Email: *

Verification: *

For which two workloads can you use computer vision? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

• A.creating visual representations of numerical data
• B.assigning the color pixels in an image to object names
• C.describing the contents of an image
• D.detecting inconsistencies and anomalies in a stream of data
• E.creating photorealistic images by using three-dimensional models

Comment: *

Name: *

Email: *

Verification: *

What is a use case for classification?

• A.predicting how many cups of coffee a person will drink based on how many hours the person slept the previous night.
• B.analyzing the contents of images and grouping images that have similar colors
• C.predicting whether someone uses a bicycle to travel to work based on the distance from home to work
• D.predicting how many minutes it will take someone to run a race based on past race times

Comment: *

Name: *

Email: *

Verification: *