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Infosys Certified Data Science using Python Professional-Part2

Practice with real exam-pattern questions for Infosys Certified Data Science using Python Professional-Part2. Each question includes a detailed explanation to help you understand the concept, not just memorise the answer. Try 10 questions free — no login required.

BeginnerData Science & Machine Learning50 min
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10 Infosys Certified Data Science using Python Professional-Part2 practice questions with answers

Real Lex exam-pattern multiple-choice questions for the Infosys Certified Data Science using Python Professional-Part2 certification. Each question includes the correct answer. The full question bank is available to Premium members.

  1. Question 1

    Select the correct range for Support and Confidence values

    • [0,1]Correct
    • B[-1,0]
    • C[-1,1]
  2. Question 2

    In the mathematical Equation of Linear Regression Y = β1 + β2X + ϵ, (β1, β2) refers to

    • (X-intercept, Slope)Correct
    • B(Slope, X-Intercept)
    • C(Y-Intercept, Slope)
    • D(slope, Y-Intercept)
  3. Question 3

    Which of the following is used when the user/item matrix contain binary values?

    • Jaccard similarity Correct
    • BCosine similarity
    • Cpearson similarity
    • DNone
  4. Question 4

    What type of data would job levels at an organization be?

    • Nominal DataCorrect
    • BOrdinal Data
    • CBinary Data
    • DContinuous Data
  5. Question 5

    The predicted rate of response of the dependent variable to changes in the independent variable is called

    • Error Correct
    • BRegression Equation
    • CSlope
    • DIntercept
  6. Question 6

    In the trade-off between bias and variance we aim for,

    • High Variance, Low Bias Correct
    • BLow Variance, High Bias
    • CLow Variance, Low Bias
    • DHigh Variance, High Bias
  7. Question 7

    A geometric interpretation of a residual is the

    • Horizontal distance from a data point to the regression line. Correct
    • BVertical distance from a data point to the regression line.
    • CPerpendicular distance from a data point to the regression line.
    • DNone
  8. Question 8

    Suppose the random variable X can take on values −1, 0, and 1 with chance p^2 , 2p(1 − p) and (1-p)^2, respectively, for 0 ≤ p ≤ 1.
    What is the expected value of X?

    • 2p(1-p) Correct
    • B1-2p
    • Cp^2
    • D0
  9. Question 9

    Which of the following functions is used to obtain the intersection of two or more dataframes?

    • mergeCorrect
    • Bconcat
    • Ciloc
    • Dreset
  10. Question 10

    Select all that apply: To determine whether the association rules discovered are sufficiently interesting enough, which of the following metrics can be used?

    • ConvictionCorrect
    • BLeverage
    • CLift
    • DCovariance
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