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What are some of the real-world scenarios where overfitting or underfitting can be problematic for model performance and accuracy? Can you share some examples?

How would you plan an experiment to investigate the addition of new emotional response buttons (e.g., 'care', 'sad') to Meta's existing 'Comment' and 'Like' options? Can you describe the development of an A/B test for this experiment?

Would you mind sharing with me a time when you failed badly and what you learned from that experience?

Please describe what techniques you would use to determine the accuracy and effectiveness of a clustering model while working with pre-existing labels.

Could you discuss the key characteristics of a perceptron?

Have you ever encountered a coin that you suspected to be biased? If so, what gave it away?

I am interested in the learning and development you gained at your previous position, which you feel will be quite valuable at Addepar

How would you craft a recommendation service that reflects a user's auditory preferences, and what historical listening details would you leverage?

What is k-means clustering? Does it find a global optimum? Implement k-means clustering, with inputs an N*D matrix and outputs k N_i*D matrices.

Tell us about the time you made a big error at work.