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NEW QUESTION 43
Which scenario is an example of a webchat bot?
- A. Translate into English questions entered by customers at a kiosk so that the appropriate person can call the customers back.
- B. From a website interface, answer common questions about scheduled events and ticket purchases for a music festival.
- C. Determine whether reviews entered on a website for a concert are positive or negative, and then add a thumbs up or thumbs down emoji to the reviews.
- D. Accept questions through email, and then route the email messages to the correct person based on the content of the message.
Answer: B
NEW QUESTION 44
You have the process shown in the following exhibit.
Which type AI solution is shown in the diagram?
- A. a computer vision application
- B. a chatbot
- C. a sentiment analysis solution
- D. a machine learning model
Answer: B
Explanation:
Section: Describe features of conversational AI workloads on Azure
NEW QUESTION 45
Which metric can you use to evaluate a classification model?
- A. mean absolute error (MAE)
- B. coefficient of determination (R2)
- C. true positive rate
- D. root mean squared error (RMSE)
Answer: C
Explanation:
Section: Describe fundamental principles of machine learning on Azure
Explanation:
What does a good model look like?
An ROC curve that approaches the top left corner with 100% true positive rate and 0% false positive rate will be the best model. A random model would display as a flat line from the bottom left to the top right corner. Worse than random would dip below the y=x line.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-understand-automated-ml#classification
NEW QUESTION 46
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 model
- B. to train multiple models simultaneously to attain better performance
- C. to train the model twice to attain better accuracy
Answer: A
Explanation:
The goal is to produce a trained (fitted) model that generalizes well to new, unknown data. The fitted model is evaluated using "new" examples from the held-out datasets (validation and test datasets) to estimate the model's accuracy in classifying new data.
https://en.wikipedia.org/wiki/Training,_validation,_and_test_sets#:~:text=Training%20dataset,- A%20training%20dataset&text=The%20goal%20is%20to%20produce,accuracy%20in%20classifying%20new%20data.
NEW QUESTION 47
You have the following dataset.
You plan to use the dataset to train a model that will predict the house price categories of houses.
What are Household Income and House Price Category? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: A feature
Box 2: A label
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/interpret-model-results
NEW QUESTION 48
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