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

If you are trying to predict or forecast a discrete target value, then which is the correct options

• A.Density estimation algorithm
• B.Supervised Learning classification algorithms
• C.Supervised Learning regression algorithms
• D.Un supervised Learning

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

• A.Ordinary Least squares
• B.Ridge and Lasso
• C.Apriori Algorithm
• D.Integer programming

Refer to image below

• A.Option D
• B.Option B
• C.Option A
• D.Option C

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

You are having 1000 patients' data with the height and age. Where age in years and height in meters. You wanted to create cluster using this two attributes. You wanted to have near equal effect for both the age and height while creating the cluster. What you can do?

• A.You will be adding height with the numeric value 100
• B.You will be dividing both age and height with their respective standard deviation
• C.You will be converting each height value to centimeters
• D.You will be taking square root of height