최신 AIP-210 무료덤프 - CertNexus Certified Artificial Intelligence Practitioner (CAIP)

문제1

A healthcare company experiences a cyberattack, where the hackers were able to reverse-engineer a dataset to break confidentiality.
Which of the following is TRUE regarding the dataset parameters?

A. The model is underfitted and trained on a high quantity of patient records.

B. The model is overfitted and trained on a low quantity of patient records.

C. The model is underfitted and trained on a low quantity of patient records.

D. The model is overfitted and trained on a high quantity of patient records.

정답: B

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문제2

Your dependent variable data is a proportion. The observed range of your data is 0.01 to 0.99. The instrument used to generate the dependent variable data is known to generate low quality data for values close to 0 and close to 1. A colleague suggests performing a logit-transformation on the data prior to performing a linear regression. Which of the following is a concern with this approach?
Definition of logit-transformation
If p is the proportion: logit(p)=log(p/(l-p))

A. Noisy data could become more influential in your model.

B. After logit-transformation, the data may violate the assumption of independence.

C. The model will be more likely to violate the assumption of normality.

D. Values near 0.5 before logit-transformation will be near 0 after.

정답: A

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문제3

Which of the following equations best represent an LI norm?

A. |x| + |y|

B. |x|+|y|^2

C. |x|^2+|y|^2

D. |x|-|y|

정답: A

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문제4

A dataset can contain a range of values that depict a certain characteristic, such as grades on tests in a class during the semester. A specific student has so far received the following grades: 76,81, 78, 87, 75, and 72.
There is one final test in the semester. What minimum grade would the student need to achieve on the last test to get an 80% average?

A. 82

B. 91

C. 94

D. 89

정답: B

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문제5

When should the model be retrained in the ML pipeline?

A. A new monitoring component is added.

B. More data become available for the training phase.

C. Some outliers are detected in live data.

D. Concept drift is detected in the pipeline.

정답: D

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문제6

When should you use semi-supervised learning? (Select two.)

A. A small set of labeled data is available but not representative of the entire distribution.

B. A small set of labeled data is biased toward one class.

C. There is a large amount of unlabeled data to be used for predictions.

D. There is a large amount of labeled data to be used for predictions.

E. Labeling data is challenging and expensive.

정답: C,E

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문제7

A company is developing a merchandise sales application The product team uses training data to teach the AI model predicting sales, and discovers emergent bias. What caused the biased results?

A. The AI model was trained in winter and applied in summer.

B. The application was migrated from on-premise to a public cloud.

C. The team set flawed expectations when training the model.

D. The training data used was inaccurate.

정답: A

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문제8

Which of the following describes a neural network without an activation function?

A. A radial basis function kernel

B. A form of a linear regression

C. An unsupervised learning technique

D. A form of a quantile regression

정답: B

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문제9

Your dependent variable Y is a count, ranging from 0 to infinity. Because Y is approximately log-normally distributed, you decide to log-transform the data prior to performing a linear regression.
What should you do before log-transforming Y?

A. Subtract the mean of Y from all the Y values.

B. Divide all the Y values by the standard deviation of Y.

C. Add 1 to all of the Y values.

D. Explore the data for outliers.

정답: C

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문제10

An organization sells house security cameras and has asked their data scientists to implement a model to detect human feces, as distinguished from animals, so they can alert th customers only when a human gets close to their house.
Which of the following algorithms is an appropriate option with a correct reason?

A. Neural network model, because this is a classification problem with a large number of features.

B. k-means, because this is a clustering problem with a small number of features.

C. A decision tree algorithm, because the problem is a classification problem with a small number of features.

D. Logistic regression, because this is a classification problem and our data is linearly separable.

정답: A

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최신 AIP-210 무료덤프 - CertNexus Certified Artificial Intelligence Practitioner (CAIP)

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