You need to make the press releases of your company available in a range of languages.
Which service should you use?

• A.Translator Text
• B.Text Analytics
• C.Speech
• D.Language Understanding (LUIS)

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/cognitive-services/custom-vision-service/home

Comment: *

Name: *

Email: *

Verification: *

You use Azure Machine Learning designer to publish an inference pipeline.
Which two parameters should you use to consume the pipeline? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

• A.the model name
• B.the training endpoint
• C.the authentication key
• D.the REST endpoint

Comment: *

Name: *

Email: *

Verification: *

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

Correct Answer:

Explanation

Privacy and security.
As AI becomes more prevalent, protecting privacy and securing important personal and business information is becoming more critical and complex. With AI, privacy and data security issues require especially close attention because access to data is essential for AI systems to make accurate and informed predictions and decisions about people. AI systems must comply with privacy laws that require transparency about the collection, use, and storage of data and mandate that consumers have appropriate controls to choose how their data is used. At Microsoft, we are continuing to research privacy and security breakthroughs (see next unit) and invest in robust compliance processes to ensure that data collected and used by our AI systems is handled responsibly.
Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

Comment: *

Name: *

Email: *

Verification: *

For a machine learning progress, how should you split data for training and evaluation?

• A.Use features for training and labels for evaluation.
• B.Randomly split the data into rows for training and rows for evaluation.
• C.Use labels for training and features for evaluation.
• D.Randomly split the data into columns for training and columns for evaluation.

Comment: *

Name: *

Email: *

Verification: *