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 algorithm independent machine learning?

125

What is the difference between artificial learning and machine learning?

105

What is the classifier in machine learning?

What are the advantages of Naive Bayes?

134

In what areas Pattern Recognition is used?

103

How would you approach the “Netflix Prize” competition?

174

What are the different methods of Sequential Supervised Learning?

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

110

What is batch statistical learning?

152

What is PAC Learning?

115

What are the different categories you can categorize the sequence learning process?

169

What is sequence learning?

109

What are two techniques of Machine Learning?

129

What is the bias-variance decomposition of classification error in the ensemble method?

147

What is an Incremental Learning algorithm in the ensemble?

109

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Un-Answered Questions { AI Machine Learning }

Explain the difference between bayes and naive bayes?

150

What is the standard approach to supervised learning?

109

Tell us when should you use classification over regression?

What is the benefit of naive bayes in machine learning?

What is feature scaling?

What is machine learning example?

What is the difference between Gini Impurity and Entropy in a Decision Tree?

235

You are given a dataset where the number of variables (p) is greater than the number of observations (n) (p>n). Which is the best technique to use and why ?

Explain the Algorithm of Neural Networks (back propagation) in Machine Learning?

111

Is python good for machine learning?

Tell us which one would you prefer to choose – model accuracy or model performance?

102

What do you mean by ensemble learning?

120

Why do we need to convert categorical variables into factor?

What are standardization and normalisation? Give one advantage of each over the other?

What does linear in ‘linear regression’ actually mean?

178

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