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Data Science MCQ

The design is the process of using data to find solutions/ to predict outcomes of a problem statement. 
It is also known as data-driven science and is an interdisciplinary field about scientific methods and processes and systems to extract knowledge or insights from data in various forms of the structured or unstructured.

There are mainly 5 stages for the data science process:

  • Understanding business problem
  • Data collection
  • Data cleaning and Exploration
  • Model building
  • Collect insights

 

Artificial intelligence, Machine learning, and Deep learning are a part of data science.

Machine learning is the Science of Getting computers to learn without being explicitly programmed.  Machine learning works on a simple concept that is understanding with experiences.

The primary aim of machine learning is to allow computers to learn automatically without human interaction.

Types of machine learning:

  • Supervised learning:
    • in supervised learning, given training explain examples of Input and corresponding output, the machine can predict outputs for new inputs
    • in supervised learning, we train the images concerning data that is well labeled and with the correct output

 

  • Unsupervised learning:
    • Unsupervised learning deals with the unlabeled data
    • No training data set is provided which means, no training will be given to the machine. Therefore it must work on its own to discover the required information.
    • The machine is trained with unlabelled data.

 

Artificial Intelligence is one of the booming fields in the computer science field, which is bringing about a global revolution by making intelligent machines. It is currently all around us in the modern world and is making an entry into every field ranging from playing chess to robotics, to self-driving cars, to proving mathematical theorems.

 Artificial Intelligence is made up of 2 words Artificial meaning “Man-Made” and Intelligence meaning “power to think”, making it a “man-made thinking machine”. The end goal of Artificial Intelligence is to make a machine that can think like humans and make decisions based on certain factors. 

Goals of Artificial Intelligence:

The main goals Artificial Intelligence aims to achieve are as follows:

  • Solve knowledge-intensive tasks.
  • Replicate human intelligence to make meaningful decisions.
  • Building a machine that can perform tasks that usually require human intelligence.
  • Build a machine that demonstrates intelligent behavior and is capable of learning new stuff from past data/experiences.

 

Data Science MCQ

1. 

Identify the language which is used in data science?

2. 

Choose the correct components of data science.

3. 

Which of the following is not a part of the data science process?

4. 

Total groups in which data can be characterized is?

5. 

Choose whether the following statement is true or false:  Unstructured data is not organized

6. 

A column is a  _________- representation of data.

7. 

Choose whether the following statement is true or false: A data frame is an unstructured representation of data

8. 

Among the following identify the one in which dimensionality reduction reduces.

9. 

Machine learning is a subset of which of the following.

10. 

FIND-S algorithm ignores?

11. 

Full form of PAC is _________________

12. 

Total types of layer in radial basis function neural networks is ______

13. 

Choose whether true or false:  Decision tree cannot be used for clustering

14. 

Procedural Domain Knowledge in a rule-based system, is in the form of?

15. 

Which of the following architecture is also known as systolic arrays?

16. 

Machines running LISP are also called?

17. 

A hybrid Bayesian Network consists of?

18. 

Identify the key data science skills among the following

19. 

Raw data should be processed only one time. Is the following statement true or false?

20. 

Identify the revision control system on the following.

21. 

Among the following options identify the one which is false regarding regression.

22. 

Choose the general limitations of the backpropagation rule among the following.

23. 

Choose the instance-based learner.

24. 

Choose whether the following statement is true or false: Artificial intelligence is the process that allows a computer to learn and make decisions like humans.

25. 

What does K stand for in K mean algorithm?

26. 

Which of the following machine learning algorithm is based upon the idea of bagging?

27. 

Choose a disadvantage of decision trees among the following.

28. 

Which of the following is not a supervised learning

29. 

Identify the clustering method which takes care of variance in data

30. 

Among the following options choose which one of the following focuses on the discovery of unknown properties on the data.

31. 

Identify the model which is  usually a gold standard for data analysis

32. 

Another name of data fishing is?

33. 

CLI stands for ___________

34. 

Choose whether the following statement is true or false:  Time deltas are differences in times, expressed in difference units

35. 

Among the following, choose the correct application of data science in Healthcare.

36. 

Identify the Incorrect CLI command.

37. 

Total principles of analytical graphs that exist are __________

38. 

Knowledge in AI can be represented as?

39. 

Inference engines work on the principle of?

40. 

Components of an expert system are?

41. 

How many types of observing environments are there?

42. 

Another name of data dredging is

43. 

Out of the given options, which of the following algorithms uses the least memory?

44. 

What are different machine learning methods?

45. 

The different types of machine learning are?

46. 

Artificial Intelligence is associated with computers of which generation?

47. 

PEAS is an abbreviation for?

48. 

Among the following SGD  variant, which of the following is based on both Momentum and adaptive learning.

49. 

Identify the activation function output which is zero centered

50. 

Among the following logic function, which of the following cannot be implemented by a  perceptron having two inputs

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