Frequently Asked Data Science Interview Questions And Answers

 Data Science Interview Questions with Answers listed here by our experts will give you a perfect guide to get through the interviews, online tests, certifications, and corporate exams. To get in-depth knowledge and frequently posted queries of the Data Science topic, just have a glance at the below questionnaire as it will really help both freshers and experienced candidates.

In this Data Science Interview Questions and answers are prepared by 10+ years of experienced industry experts. Data Science Interview Questions and answers are very useful to the Fresher or Experienced person who is looking for a new challenging job from the reputed company.

Frequently Asked Data Science Interview Questions And Answers

By this Data Science Interview Questions and answers, many students are got placed in many reputed companies with high package salaries. So utilize our Data Science Interview Questions and answers to grow in your career.

Q31. What is the F1 score?

Answer: The F1 score is defined as a measure of a model's performance .

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Q32. How is F1 score is used?

Answer: The average of Precision and Recall of a model is nothing but F1 score measure. Based on the results,the F1 score is 1 then it is classified as best and 0 being the worst.

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Q33. What is the difference between Machine learning Vs Data Mining?

Answer: Data mining is about working on unlimited data and then extract it to a level anywhere the unusual and unknown patterns are identified.
Machine learning is any method about a study whether it closely relates to design, development concerning the algorithms that provide an ability to certain computers to capacity to learn.

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Q34. What are confounding variables?

Answer: These are obvious variables in a scientific model that correlates directly or inversely with both the subject and the objective variable. The study fails to account for the confounding factor.

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Q35.How can you randomize the items of a list in place in Python?

Answer: Consider the example shown below: from random import shuffle

x = [ Data , Class , Blue , Flag , Red , Slow ]
shuffle(x)
print(x)
    

The output of the following code is as below.

[ Red , Data , Blue , Slow , Class , Flag ]

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Q36. How to get indices of N maximum values in a NumPy array?

Answer: We can get the indices of N maximum values in a NumPy array using the below code:

import numpy as np
arr = np.array([1, 3, 2, 4, 5])
print(arr.argsort()[-3:][::-1])
Output
[ 4 3 1 ]
  

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Q37. How make you 3D plots/visualizations using NumPy/SciPy?

Answer:
Like 2D plotting, 3D graphics is beyond the scope of NumPy and SciPy, but just as in this 2D example, packages exist that integrate with NumPy.
Matplotlib provides primary 3D plotting in the mplot3d subpackage, whereas Mayavi produces a wide range of high-quality 3D visualization features, utilizing the powerful VTK engine.

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Q38. What are the types of biases that can occur during sampling?

Answer:
Some simple models of selection bias are described below.
Undercoverage occurs when some members of the population live badly represented in side the sample & The telephone directories and car registration lists.

• Selection bias
• Under coverage bias
• Survivorship bias

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Q39. Which Python library is used for data visualization?

Answer:
Plotly. The fifth tool is Plotly, also called as Plot.ly because of its main platform online. It is an interactive online visualization tool that is being used for data analytics, scientific graphs, and other visualization. This contains some great API including one for Python

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Q40. How to access a specific script inside a module?

Answer:
If the whole module needs to be imported, we simply can use from pandas import *

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