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NEW QUESTION 30
When training a model, why should you randomly split the rows into separate subsets?

A. to test the model by using data that was not used to train the modelB. to train multiple models simultaneously to attain better performanceC. to train the model twice to attain better accuracy

Answer: A

Explanation:
Section: Describe fundamental principles of machine learning on Azure

 

NEW QUESTION 31
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://azure.microsoft.com/es-es/blog/machine-assisted-text-classification-on-content-moderator-public-preview/
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing

 

NEW QUESTION 32
You build a machine learning model by using the automated machine learning user interface (UI).
You need to ensure that the model meets the Microsoft transparency principle for responsible AI.
What should you do?

A. Set Validation type to Auto.B. Set Max concurrent iterations to 0.C. Enable Explain best model.D. Set Primary metric to accuracy.

Answer: C

Explanation:
Model Explain Ability.
Most businesses run on trust and being able to open the ML "black box" helps build transparency and trust. In heavily regulated industries like healthcare and banking, it is critical to comply with regulations and best practices. One key aspect of this is understanding the relationship between input variables (features) and model output. Knowing both the magnitude and direction of the impact each feature (feature importance) has on the predicted value helps better understand and explain the model. With model explain ability, we enable you to understand feature importance as part of automated ML runs.
Reference:
https://azure.microsoft.com/en-us/blog/new-automated-machine-learning-capabilities-in-azure-machine-learning-service/

 

NEW QUESTION 33
You are developing a natural language processing solution in Azure. The solution will analyze customer reviews and determine how positive or negative each review is.
This is an example of which type of natural language processing workload?

A. sentiment analysisB. entity recognitionC. key phrase extractionD. language detection

Answer: A

Explanation:
Explanation
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing

 

NEW QUESTION 34
Your company wants to build a recycling machine for bottles. The recycling machine must automatically identify bottles of the correct shape and reject all other items.
Which type of AI workload should the company use?

A. conversational AIB. natural language processingC. anomaly detectionD. computer vision

Answer: D

Explanation:
Section: Describe features of computer vision workloads on Azure
Explanation:
Azure's Computer Vision service gives you access to advanced algorithms that process images and return information based on the visual features you're interested in. For example, Computer Vision can determine whether an image contains adult content, find specific brands or objects, or find human faces.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview

 

NEW QUESTION 35
......

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