Data Science Interview Questions
Questions Answers Views Company eMail

What are the applications of data science?

127

What is the difference between data science, machine learning and artificial intelligence?

111

Can you define cluster sampling?

91

Can you explain systematic sampling?

102

Can you define linear regression?

96

Can you define analytics?

93

What is the differences between univariate, bivariate and multivariate analysis?

129

Can you explain root cause analysis?

88

Can you write the formula to calculate r-square?

101

Can you explain k-mean?

84

Why is data munging useful?

90

Can you define data reduction?

74

Can you define convex hull?

91

Can you explain recommender system?

95

Can you explain data preparation?

100


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Un-Answered Questions { Data Science }

How have you overcome a barrier to finding a solution?

87


Explain why data cleansing is essential and which method you use to maintain clean data?

103


Explain about the various time series forecasting technqiues.

105


If you had to choose between the programming languages r and python, which one would you use for text analytics?

103


Can you explain systematic sampling?

102






What functions are required to principal analysis in R?

184


What are the feature vectors?

94


What is the correlation in r?

78


What are numpy, scipy, and spark essential datatypes?

103


Differentiate between regression and classification algorithms?

105


Explain how to operate on file and directory?

95


What is the svm algorithm?

107


Explain data preparation?

87


What kind of product you want to build at LinkedIn?

95


What motivates you to transition from academia to data science?

101