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What is Linear Regression? What are the assumptions of a Linear Regression Model?
Machine Learning Basics
What is Regularization? When do we need it?
Machine Learning Basics, Deep Learning Basics
What is Ensemble Learning? How many types of ensemble methods are there?
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?
What are Gaussian Mixture Models? Explain how it works.
Advanced Machine Learning
Explain Expectation-Maximization Algorithm.
Advanced Deep Learning
Explain Back-propagation and it's advantages.
Deep Learning Basics
Explain how Support Vector Machine (SVM) works? Describe Optimization of Hinge Loss in terms of lagrange.
Explain K-Means Algorithm? How to select optimal value of "k" it? Does k-means converge to a global solution?
Explain the Decision Tree algorithm. What are Entropy and Information gain in Decision Tree algorithm?