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Databricks-Certified-Professional-Data-Scientist Databricks Certified Professional Data Scientist Exam Questions and Answers

Questions 4

Which of the following could be features?

Options:

A.

Words in the document

B.

Symptoms of a diseases

C.

Characteristics of an unidentified object

D.

0nly 1 and 2

E.

All 1,2 and 3 are possible

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Questions 5

Suppose that we are interested in the factors that influence whether a political candidate wins an election. The outcome (response) variable is binary (0/1); win or lose. The predictor variables of interest are the amount of money spent on the campaign, the amount of time spent campaigning negatively and whether or not the candidate is an incumbent.

Above is an example of

Options:

A.

Linear Regression

B.

Logistic Regression

C.

Recommendation system

D.

Maximum likelihood estimation

E.

Hierarchical linear models

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Questions 6

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

Options:

A.

P(E1)/P(E2)

B.

P(E1+E2)/P(E1)

C.

P(E2)/P(E1)

D.

P(E2)/(P(E1+E2)

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Questions 7

Classification and regression are examples of___________.

Options:

A.

supervised learning

B.

un-supervised learning

C.

Clustering

D.

Density estimation

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Questions 8

In which phase of the analytic lifecycle would you expect to spend most of the project time?

Options:

A.

Discovery

B.

Data preparation

C.

Communicate Results

D.

Operationalize

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Questions 9

Suppose you have made a model for the rating system, which rates between 1 to 5 stars. And you calculated that RMSE value is 1.0 then which of the following is correct

Options:

A.

It means that your predictions are on average one star off of what people really think

B.

It means that your predictions are on average two star off of what people really think

C.

It means that your predictions are on average three star off of what people really think

D.

It means that your predictions are on average four star off of what people really think

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Questions 10

Clustering is a type of unsupervised learning with the following goals

Options:

A.

Maximize a utility function

B.

Find similarities in the training data

C.

Not to maximize a utility function

D.

1 and 2

E.

2 and 3

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Questions 11

What is the probability that the total of two dice will be greater than 8, given that the first die is a 6?

Options:

A.

1/3

B.

2/3

C.

1/6

D.

2/6

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Questions 12

Question-34. Stories appear in the front page of Digg as they are "voted up" (rated positively) by the community. As the community becomes larger and more diverse, the promoted stories can better reflect the average interest of the community members. Which of the following technique is used to make such recommendation engine?

Options:

A.

Naive Bayes classifier

B.

Collaborative filtering

C.

Logistic Regression

D.

Content-based filtering

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Questions 13

Which method is used to solve for coefficients bO, b1, ... bn in your linear regression model:

Options:

A.

Apriori Algorithm

B.

Ridge and Lasso

C.

Ordinary Least squares

D.

Integer programming

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Questions 14

Refer to the Exhibit.

In the Exhibit, the table shows the values for the input Boolean attributes "A", "B", and "C". It also shows the values for the output attribute "class". Which decision tree is valid for the data?

Options:

A.

Tree A

B.

Tree B

C.

Tree C

D.

Tree D

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Questions 15

A researcher is interested in how variables, such as GRE (Graduate Record Exam scores), GPA (grade point average) and prestige of the undergraduate institution, effect admission into graduate school. The response variable, admit/don't admit, is a binary variable.

Above is an example of

Options:

A.

Linear Regression

B.

Logistic Regression

C.

Recommendation system

D.

Maximum likelihood estimation

E.

Hierarchical linear models

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Questions 16

What describes a true limitation of Logistic Regression method?

Options:

A.

It does not handle redundant variables well.

B.

It does not handle missing values well.

C.

It does not handle correlated variables well.

D.

It does not have explanatory values.

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Questions 17

You are asked to create a model to predict the total number of monthly subscribers for a specific magazine. You are provided with 1 year's worth of subscription and payment data, user demographic data, and 10 years worth of content of the magazine (articles and pictures). Which algorithm is the most appropriate for building a predictive model for subscribers?

Options:

A.

Linear regression

B.

Logistic regression

C.

Decision trees

D.

TF-IDF

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Questions 18

What are the key outcomes of the successful analytical projects?

Options:

A.

Code of the model

B.

Technical specifications

C.

Presentations for the Analysts

D.

Presentation for Project Sponsors

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Questions 19

Spam filtering of the emails is an example of

Options:

A.

Supervised learning

B.

Unsupervised learning

C.

Clustering

D.

1 and 3 are correct

E.

2 and 3 are correct

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Questions 20

You are using one approach for the classification where to teach the agent not by giving explicit categorizations, but by using some sort of reward system to indicate success, where agents might be rewarded for doing certain actions and punished for doing others. Which kind of this learning

Options:

A.

Supervised

B.

Unsupervised

C.

Regression

D.

None of the above

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Exam Name: Databricks Certified Professional Data Scientist Exam
Last Update: Nov 3, 2024
Questions: 138
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