Data Science Quiz


Play this quiz that will help you to excel in Data Science certification exams, placements etc. This Data Science quiz consist of 10 questions that you need to solve in 10 minutes. We’ve specially designed this quiz so that you can quickly acquaint to the pattern of questions you can be asked in placement drives, certification exams etc. This Data Science test enables you to assess your knowledge of Data Science.

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Data Science MCQs

Practice Data Science MCQ Questions, which will help you to improve your data science skills and also helps you to prepare for placements, technical rounds, interviews, competitive exams etc.

Data Science Quiz

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Data Science Quiz

1. In Model based learning methods, an iterative process takes place on the ML models that are built based on various model parameters, called ?

mini-batches
optimizedparameters
hyperparameters
superparameters

2. Raw data should be processed only one time.

True
False
Can be true or false
Can not say

3. Deep learning algorithms are _______ more accurate than machine learning algorithm in image classification.

33%
37%
40%
41%

4. Which of the following statement is false?

ndarray is also known as the axis array.
ndarray.dataitemSize is the buffer containing the actual elements of the array.
NumPy main object is the homogeneous multidimensional array
In Numpy, dimensions are called axes

5. SciPy Original author is?

Guido van Rossum
Travis Oliphant
Wes McKinney
Jim Hugunin

6. Which of the following thing can be data in Pandas?

a python dict
an ndarray
a scalar value
All of the above

7. Which of the following statement is true?

Some ufuncs can take output arguments.
Broadcasting is used throughout NumPy to decide how to handle disparately shaped arrays
Many of the built-in functions are implemented in compiled C code
The array object returned by __array_prepare__ is passed to the ufunc for computation.

8. What is the value of unit milli in SciPy?

0.01
0.1
0.0001
0.001

9. Why ndim is used?

Returns the number of elements in the underlying data.
Returns the Series as ndarray.
Returns the number of dimensions of the underlying data, by definition 1.
Returns a list of the axis labels

10. What will be output for the following code?

import numpy as np 

a = np.array([1,2,3]) 

print a

[[1, 2, 3]]
[1]
[1, 2, 3]
Error

Results