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

How is KNN different from K-means clustering?

120

What is ROC curve and what does it represent?

What’s the difference between Type I and Type II error?

144

Is it better to have too many false positives or too many false negatives? Explain.

Which is more important to you – model accuracy or model performance?

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

218

What is the difference between Entropy and Information Gain?

124

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

Explain Ensemble learning technique in Machine Learning?

116

What is bagging and boosting in Machine Learning?

178

What is bagging in Machine Learning?

What is boosting in Machine Learning?

How would you screen for outliers and what should you do if you find one?

103

What are collinearity and multicollinearity?

109

What do you understand by Eigenvectors and Eigenvalues?

110

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Un-Answered Questions { AI Machine Learning }

What is bagging in Machine Learning?

What are the three stages to build any model in machine learning?

Why Accuracy is important in machine learning?

164

What is data pre-processing technique for machine learning?

Why is manhattan distance not used in knn machine learning algorithm to calculate the distance between nearest neighbors?

165

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

What is Cluster Sampling in Machine Learning?

108

What is ‘tuning’ in ML?

What is semi-supervised Machine Learning?

How are NumPy and SciPy related?

127

Who invented machine learning?

Tell me how a roc curve works?

What do you understand by cluster sampling?

What are the necessary steps involved in machine learning project?

171

What are the various aspects of a machine learning process?

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