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Precision and recall are two common metrics used to evaluate the performance of classification models. Can you explain what they measure and how they are calculated? Also, discuss some situations where these metrics may not be suitable for assessing model accuracy.

Can you think of a way to explain power to someone who doesn't understand technical terms?

See if you can identify the anagrams among these words - Silent, Listen, Race, Care.

What benchmarks do you utilize for measuring computer vision model performance?

What's the difference between the summaries of a Logistic Regression and SVM?

Why are you looking for a job at the moment?

To ascertain how well a model is functioning, one can calculate the AUC. How would you suggest we go about calculating AUC for our model?

Would you mind explaining Markov Chains in terms that are accessible to the everyday person?

Could you explain why your ideal company might be AT&T?

Could you develop a Python function that applies a markdown to selected song streams?