Data Science Interview Questions

What will you do if removing missing values from a dataset cause bias?

17

How can you reduce bias in a given data set?

28

How will you impute missing information in a dataset?

19

Estimate the probability of a disease in a particular city given that the probability of the disease on a national level is low.

19

How will inspect missing data and when are they important for your analysis?

22

How will you decide whether a customer will buy a product today or not given the income of the customer, location where the customer lives, profession and gender? Define a machine learning algorithm for this.

19

From a long sorted list and a short 4 element sorted list, which algorithm will you use to search the long sorted list for 4 elements.

15

How can you compare a neural network that has one layer, one input and output to a logistic regression model?

15

How do you treat colinearity?

24

How will you deal with unbalanced data where the ratio of negative and positive is huge?

15

What is the difference between Stack and Queue

28

What is the difference between Linkedin and Array

13

You are about to get on a plane to Seattle, you want to know whether you have to bring an umbrella or not. You call three of your random friends and as each one of them if it's raining. The probability that your friend is telling the truth is 2/3 and the probability that they are playing a prank on you by lying is 1/3. If all 3 of them tell that it is raining, then what is the probability that it is actually raining in Seattle.

16

You have been given the data on Facebook user's friending or defriending each other. How will you determine whether a given pair of Facebook users are friends or not?

18

Estimate the number of square feet pizza's eaten in US each year.

13

Un-Answered Questions { Data Science }

Explain how to define the number of clusters in a clustering algorithm?

18

what is the difference between extrapolation and interpolation?

14

How will you compare the results of various machine learning algorithms?

31

What are the feature vectors?

11

How to work towards a random forest?

11

What is an outlier? How do you treat outlier data?

3

What is need of principal component analysis?

53

A disc is spinning on a spindle and you don't know the direction in which way the disc is spinning. You are provided with a set of pins.How will you use the pins to describe in which way the disc is spinning?

14

If we added one rider to the current SF market, how would that affect the existing riders and drivers?

40

How do you handle missing values in python or r?

14

Explain the method to collect and analyze data to use social media to predict the weather condition?

13

How will you decide whether a customer will buy a product today or not given the income of the customer, location where the customer lives, profession and gender? Define a machine learning algorithm for this.

19

Explain the goal of a/b testing?

11

Explain eigenvalue and eigenvector

11

How regularly must an algorithm be updated?

12