How will you explain machine learning into a layperson?

67

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What do you mean by parametric models? Also, give some examples of them?

70

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Why do we convert categorical variables into factor?

104

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What type of learning is needed when the system needs to adapt to rapidly changing data?

126

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How to decide one problem is a machine learning problem or not?

194

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What is the sigmoid function in machine learning?

114

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Give a drawback of gradient descent ?

84

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Logistic regression gives probabilities as a result then how do we use it to predict a binary outcome?

71

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What is adagrad algorithm in machine learning?

106

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What kind of problems lend themselves to machine learning?

67

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What is the difference between supervised and unsupervised learning?

98

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Which one would you prefer to choose – model accuracy or model performance?

185

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What are standardization and normalisation?

107

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What is bias-variance trade-off in machine learning?

95

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Does 100% precision mean that our model predicts all the values correctly?

66

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