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26. What is Regularization? When do we need it?
Machine Learning Basics, Deep Learning Basics
Easy
28. What is ROC Curve? What is the interpretation of an ROC area under the curve? What is the difference between the PR(Precision-Recall) curve and the ROC curve?
Medium
31. Explain Back-propagation and it's advantages.
Deep Learning Basics
32. Explain how Support Vector Machine (SVM) works? Describe Optimization of Hinge Loss in terms of lagrange.
Advanced Machine Learning
33. Explain K-Means Algorithm? How to select optimal value of "k" it? Does k-means converge to a global solution?
34. Explain the Decision Tree algorithm. What are Entropy and Information gain in Decision Tree algorithm?
Advanced Deep Learning
38. What is a P-value, and how to interpret them?
Machine Learning Basics, Probability
39. What are Type I and Type II errors? How to avoid them?
Machine Learning Basics
42. Describe how gradient boosting works.
45. Explain the difference between bagging and boosting models.