Free Online Databricks Databricks-Certified-Professional-Data-Scientist Practice Test

Prepare Your Databricks Databricks-Certified-Professional-Data-Scientist Exam Questions with Free online Databricks-Certified-Professional-Data-Scientist Practice Test. Get Brilliant Databricks Certified Professional Data Scientist Exam Results with Valid Databricks Certified Professional Data Scientist Exam Dumps.

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Total 140 Questions | Updated On: May 15, 2024

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Question 1

Assume some output variable "y" is a linear combination of some independent input variables "A" plus some

independent noise "e". The way the independent variables are combined is defined by a parameter vector B

y=AB+e where X is an m x n matrix. B is a vector of n unknowns, and b is a vector of m values. Assuming

that m is not equal to n and the columns of X are linearly independent, which expression correctly solves for

A :

B :

C :

D :

Answer: D

Question 2

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(A|B,C)

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

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

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

Answer: A

Question 3

You are designing a recommendation engine for a website where the ability to generate more personalized recommendations by analyzing information from the past activity of a specific user, or the history of other users deemed to be of similar taste to a given user. These resources are used as user profiling and helps the site recommend content on a user-by-user basis. The more a given user makes use of the system, the better the recommendations become, as the system gains data to improve its model of that user. What kind of this recommendation engine is ?

A : Naive Bayes classifier

B : Collaborative filtering

C : Logistic Regression

D : Content-based filtering

Answer: B

Question 4

Select the sequence of the developing machine learning applications

A) Analyze the input data

B) Prepare the input data

C) Collect data

D) Train the algorithm

E) Test the algorithm

F) Use It

A : A, B, C, D, E, F

B : C, B, A, D, E, F

C : C, A, B, D, E, F

D : C, B, A, D, E, F

Answer: D

Question 5

You are creating a model for the recommending the book at Amazon.com, so which of the following

recommender system you will use you don't have cold start problem?

A : Naive Bayes classifier

B : Item-based collaborative filtering

C : User-based collaborative filtering

D : Content-based filtering

Answer: D

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Total 140 Questions | Updated On: May 15, 2024

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