[2026] Databricks Certified Professional Data Scientist - Databricks-Certified-Professional-Data-Scientist 무료 시험 문제

문제1

You are studying the behavior of a population, and you are provided with multidimensional data at the individual level. You have identified four specific individuals who are valuable to your study, and would like to find all users who are most similar to each individual. Which algorithm is the most appropriate for this study?

A. K-means clustering

B. Decision trees

C. Association rules

D. Linear regression

정답: A

설명: (Fast2test 회원만 볼 수 있음)

문제2

Select the correct option from the below

A. If you're not trying to predict a target value, then you need to look into unsupervised learning

B. If the target value can take on a number of values, say any value from 0.00 to 100.00, or -999 to 999: or
+_to -_, then you need to look unsupervised learning

C. Are you trying to fit your data into some discrete groups? If so and that's all you need, you should look into clustering.

D. If you're trying to predict or forecast a target value^ then you need to look into supervised learning.

E. If you've chosen supervised learning, with discrete target value like Yes/No. 1/2/3, A/B/C: or Red/Yellow/Black, then look into classification.

정답: A,C,D,E

설명: (Fast2test 회원만 볼 수 있음)

문제3

What type of output generated in case of linear regression?

A. Values between 0 and 1

B. Continuous variable

C. Discrete Variable

D. Any of the Continuous and Discrete variable

정답: B

설명: (Fast2test 회원만 볼 수 있음)

문제4

Support vector machines (SVMs) are a set of supervised learning methods used for

A. Linear classification

B. Regression

C. Non-linear classification

정답: A,B,C

설명: (Fast2test 회원만 볼 수 있음)

문제5

Digit recognition, is an example of.....

A. Unsupervised learning

B. Clustering

C. Classification

D. None of the above

정답: C

설명: (Fast2test 회원만 볼 수 있음)

문제6

Suppose you have been given two Random Variables X and Y, whose joint distribution is already known, the marginal distribution of X is simply the probability distribution of X averaging over information about Y.
It is the probability distribution of X when the value of Y is not known. So how do you calculate the marginal distribution of X

A. This is typically calculated by summing (In case of discrete variable) the joint probability distribution over Y

B. This is typically calculated by integrating the joint probability distribution over Y

C. This is typically calculated by summing the joint probability distribution over Y.

D. This is typically calculated by integrating(ln case of continuous variable) the joint probability distribution over Y.

정답: A,B,C,D

설명: (Fast2test 회원만 볼 수 있음)

문제7

What is the best way to evaluate the quality of the model found by an unsupervised algorithm like k-means clustering, given metrics for the cost of the clustering (how well it fits the data) and its stability (how similar the clusters are across multiple runs over the same data)?

A. The most stable clustering subject to a minimal cost constraint

B. The most stable clustering

C. The lowest cost clustering

D. The lowest cost clustering subject to a stability constraint

정답: D

설명: (Fast2test 회원만 볼 수 있음)

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