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AI Machine Learning Interview Questions
Questions Answers Views Company eMail

What is the meaning of overfitting in machine learning?

 51

What do you understand by machine learning?

 85

Why overfitting occurs?

 53

Differentiate between inductive learning and deductive learning?

 72

When does regularization become necessary in machine learning?

 78

What are the five popular algorithms we use in machine learning?

 52

What are the functions of unsupervised learning?

 50

What do you understand by decision tree in machine learning?

 53

What is regularization? What kind of problems does regularization solve?

 46

What do you understand by underfitting?

 61

Why do we need to convert categorical variables into factor? Which functions are used to perform the conversion?

 51

What are the similarities and differences between bagging and boosting in machine learning?

 54

What do you understand by the f1 score?

 50

What do you understand by cluster sampling?

 35

What are the necessary steps involved in machine learning project?

 82

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Un-Answered Questions { AI Machine Learning }

Mention any one of the data visualization tools that you are familiar with?

41

What is the benefit of naïve bayes mcq?

50

What is not Machine Learning?

59

What is the difference between artificial intelligence and machine learning?

69

Explain the function of Unsupervised Learning?

53




Which is the best language for machine learning?

49

What do you understand by selection bias?

143

What are two techniques of Machine Learning?

83

How do we know which machine learning algorithm is better for us to solve our problem?

44

Explain false negative, false positive, true negative and true positive with a simple example?

60

Why do we need a validation set and test set? What is the difference between them?

71

Why do we convert categorical variables into factor?

48

Tell me what is precision and recall?

76

Which method is frequently used to prevent overfitting?

43

Why machine learning?

51

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