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How is KNN different from K-means clustering?
What is ROC curve and what does it represent?
What’s the difference between Type I and Type II error?
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?
What is the difference between Entropy and Information Gain?
What is Overfitting? And how do you ensure you’re not overfitting with a model?
Explain Ensemble learning technique in Machine Learning?
What is bagging and boosting in Machine Learning?
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?
What are collinearity and multicollinearity?
What do you understand by Eigenvectors and Eigenvalues?
