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What are some of the optimization techniques you’ve worked with or studied? What is your methodology for optimizing a function that includes a million variables? Can you describe the procedural steps of the simplex method used for optimization?

Create a distributed framework for performing A/B testing at scale.

Can we consider R-square to be an all-encompassing measure for linear regression model accuracy? When faced with a low R-square measurement, how do you assess the adequacy of the regression model?

Illustrate how the Monte Carlo method can estimate the value of Pi.

How would you summarize the basic actions taken during backpropagation in a neural network model?

Could you devise a binary search method for extracting the maximum integer from a list?

Differentiate between RNN and LSTM.

Hyperparameter tuning is a critical step in machine learning. Can you compare and contrast grid search CV and random search CV for optimizing hyperparameters?

What are the factors that determine the time complexity of SVM training? How does the time complexity during SVM inference compare to its training time complexity? What are the time complexity implications of using different kernels like Linear and RBF in SVMs?

What methods have you employed to tackle multicollinearity in your models?