AI Machine Learning Interview Questions, Answers for Freshers and Experienced asked in various Company Job Interviews

AI Machine Learning Interview Questions

Questions Answers Views Company eMail

What is the meaning of overfitting in machine learning?

106

What do you understand by machine learning?

117

Why overfitting occurs?

117

Differentiate between inductive learning and deductive learning?

107

When does regularization become necessary in machine learning?

210

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

175

What are the functions of unsupervised learning?

What do you understand by decision tree in machine learning?

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

What do you understand by underfitting?

116

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

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

What do you understand by the f1 score?

What do you understand by cluster sampling?

What are the necessary steps involved in machine learning project?

179

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Un-Answered Questions { AI Machine Learning }

Can you explain bias-variance trade-off?

126

How do I become an expert in machine learning?

101

Explain the purpose of a classifier?

How to handle missing data in a dataset in Machine Learning?

164

What is Overfitting? And how do you ensure you’re not overfitting with a model?

111

How does machine learning differ from deep learning?

What is Inductive Logic Programming in Machine Learning?

140

Explain what is the function of ‘Supervised Learning’?

How will you choose the most appropriate machine learning algorithm for your classification problem?

Mention key business metrics that help ML?

111

Is Python enough for machine learning?

109

Is java used for ai?

174

What is pruning in decision trees and how is it done?

104

What is Random Forest?

117

Tell me what is the difference between bias and variance?

122

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