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Can you outline the benefits and limitations of SVMs?

How does PCA dissect and condense the feature space?

In your experience, what are some of the examples of real-world scenarios where overfitting and underfitting have posed challenges for model performance and accuracy? What are the outcomes?

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?

What is your understanding of an attention model?

There are multiple ways to perform hyperparameter tuning with machine learning algorithms. Can you explain the differences between grid search CV and random search CV?

Before applying machine learning algorithms, what are some of the things you have to do in terms of data wrangling and cleaning?

How would you construct a solution to find the longest palindrome within a provided string?