최신 Databricks-Certified-Professional-Data-Scientist 무료덤프 - Databricks Certified Professional Data Scientist

문제1

As a data scientist consultant at ABC Corp, you are working on a recommendation engine for the learning resources for end user. So Which recommender system technique benefits most from additional user preference data?

A. Naive Bayes classifier

B. Content-based filtering

C. Logistic Regression

D. Item-based collaborative filtering

정답: D

설명: (DumpTOP 회원만 볼 수 있음)

문제2

Suppose A, B , and C are events. The probability of A given B , relative to P(|C), is the same as the probability of A given B and C (relative to P ). That is,

A. P(A,B|C) P(B|C) =P(B|A,C)

B. P(A,B|C) P(B|C) =P(C|B,C)

C. P(A,B|C) P(B|C) =P(A|B,C)

D. P(A,B|C) P(B|C) =P(A|C,B)

정답: C

설명: (DumpTOP 회원만 볼 수 있음)

문제3

Select the correct statement which applies to K-Nearest Neighbors

A. Computationally expensive

B. Require less memory

C. Works with Numeric Values

D. No Assumption about the data

정답: A,C,D

설명: (DumpTOP 회원만 볼 수 있음)

문제4

Spam filtering of the emails is an example of

A. Unsupervised learning

B. Clustering

C. 2 and 3 are correct

D. Supervised learning

E. 1 and 3 are correct

정답: D

설명: (DumpTOP 회원만 볼 수 있음)

문제5

Which of the following could be features?

A. Symptoms of a diseases

B. Characteristics of an unidentified object

C. Words in the document

D. All 1,2 and 3 are possible

E. 0nly 1 and 2

정답: D

설명: (DumpTOP 회원만 볼 수 있음)

문제6

Select the correct statement regarding the naive Bayes classification

A. it only requires a small amount of training data to estimate the parameters

B. Independent variables can be assumed

C. only the variances of the variables for each class need to be determined

D. for each class entire covariance matrix need to be determined

정답: A,B,C

설명: (DumpTOP 회원만 볼 수 있음)

문제7

If E1 and E2 are two events, how do you represent the conditional probability given that E2 occurs given that E1 has occurred?

A. P(E2)/P(E1)

B. P(E2)/(P(E1+E2)

C. P(E1)/P(E2)

D. P(E1+E2)/P(E1)

정답: A

문제8

Which technique you would be using to solve the below problem statement? "What is the probability that individual customer will not repay the loan amount?"

A. Linear Regression

B. Clustering

C. Hypothesis testing

D. Classification

E. Logistic Regression

정답: E

문제9

Your customer provided you with 2. 000 unlabeled records three groups. What is the correct analytical method to use?

A. Logistic regression

B. Semi Linear Regression

C. K-means clustering

D. Linear regression

E. Naive Bayesian classification

정답: C

설명: (DumpTOP 회원만 볼 수 있음)

문제10

Regularization is a very important technique in machine learning to prevent overfitting. Mathematically speaking, it adds a regularization term in order to prevent the coefficients to fit so perfectly to overfit. The difference between the L1 and L2 is...

A. L1 is the sum of the square of the weights, while L2 is just the sum of the weights

B. L1 gives Non-sparse output while L2 gives sparse outputs

C. None of the above

D. L2 is the sum of the square of the weights, while L1 is just the sum of the weights

정답: D

설명: (DumpTOP 회원만 볼 수 있음)

최신 Databricks-Certified-Professional-Data-Scientist 무료덤프 - Databricks Certified Professional Data Scientist

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