Most Recent Databricks-Certified-Professional-Data-Scientist Exam Questions & Answers

Prepare for the Databricks Certified Professional Data Scientist Exam exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.

QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Databricks-Certified-Professional-Data-Scientist exam and achieve success.

The questions for Databricks-Certified-Professional-Data-Scientist were last updated on Jan 17, 2025.

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Question No. 1

Select the correct statement which applies to logistic regression

AComputationally inexpensive, easy to implement knowledge representation easy to interpret

BMay have low accuracy

CWorks with Numeric values

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Correct Answer: A, B, C

Question No. 2

Logistic regression is a model used for prediction of the probability of occurrence of an event. It makes use of several variables that may be......

ANumerical

BCategorical

CBoth 1 and 2 are correct

DNone of the 1 and 2 are correct
Logistic regression is a model used for prediction of the probability of occurrence of an event. It makes use of several predictor variables that may be either numerical or categories.

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Correct Answer: C

Question No. 3

Select the correct option which applies to L2 regularization

AComputational efficient due to having analytical solutions

BNon-sparse outputs

CNo feature selection

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Correct Answer: A, B, C

The difference between their properties can be promptly summarized as follows:

Question No. 4

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

AApriori Algorithm

BRidge and Lasso

COrdinary Least squares

DInteger programming

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Correct Answer: C

In the linear model, the bi's represent the unknown p parameters. The estimates for these unknown parameters are chosen so that, on average, the model provides a reasonable estimate of a person's income based on age and education. In other words, the fitted model should minimize the overall error between the linear model and the actual observations. Ordinary Least Squares (OLS) is a common technique to estimate the parameters

Question No. 5

You are working on a email spam filtering assignment, while working on this you find there is new word e.g. HadoopExam comes in email, and in your solutions you never come across this word before, hence probability of this words is coming in either email could be zero. So which of the following algorithm can help you to avoid zero probability?

ANaive Bayes

BLaplace Smoothing

CLogistic Regression

DAll of the above
Laplace smoothing is a technique for parameter estimation which accounts for unobserved events. It is more robust and will not fail completely when data that has never been observed in training shows up.

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Correct Answer: B

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