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As a data scientist, how do you approach hyperparameter tuning? Can you compare and contrast grid search CV and random search CV?

Why is outlier detection essential in data science and machine learning?

Can you mention a selection of optimization algorithms you're versed in? How would you go about optimizing a scenario with an extremely large variable set, say a million? How does the simplex method facilitate solving linear optimization problems?

Can you explain the process of k-means clustering and whether it assures a global optimum solution? Additionally, demonstrate how you would implement this with an N*D matrix.

If you were ever the manager of a team, tell me about it

Why are researchers and data scientists increasingly interested in dimensionality reduction, and what problems does it solve?

How does the R-square measure fall short in providing a complete picture of linear regression model performance? What does it imply about the linear regression model when you encounter a low R-square?

How to decompose errors into variance and bias?

How would you go about calculating the shortest distance from A to B for a knight on an infinite chessboard?

You are given an array of integers, and you are asked to determine the subarray of length k with the maximum possible sum. How would you approach this task?