AI Machine Learning Interview Questions
Questions Answers Views Company eMail

Why naïve bayes is called naïve?

67

What are the 3 types of ai?

51

Explain the objective of machine learning?

84

Explain the machine learning techniques?

39

Explain the types of machine learning?

69

What is regression in machine learning?

76

Explain the difference between machine learning and regression?

50

What is conditional probability?

63

Explain the difference between bayes and naive bayes?

67

How bayes theorem is useful in a machine learning context?

60

What are the classification problems in machine learning?

74

Explain why is naive bayes better than decision tree?

47

Explain the benefit of naive bayes in machine learning?

77

Why naive bayes is called naive?

56

Explain the difference between bayesian and frequentist?

65


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Un-Answered Questions { AI Machine Learning }

What is your training in machine learning and what types of hands-on experience do you have?

42


What are the areas in robotics and information processing where the sequential prediction problem arises?

64


What is classifier in machine learning?

56


What is Perceptron in Machine Learning?

69


What is the purpose of a classifier?

45






Do you know what's the “kernel trick” and how is it useful?

50


What is a binary classification in machine learning?

49


Tell me what is supervised versus unsupervised learning?

52


What do you mean by genetic programming?

72


How can we use your machine learning skills to generate revenue?

71


What do you understand by decision tree in machine learning?

53


What is accuracy score in machine learning?

76


What is symbolic machine learning?

73


What do you understand by Eigenvectors and Eigenvalues?

62


How many types are available in machine learning?

98