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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 demonstrate an algorithm to combine two sorted arrays into one that remains sorted?

Given a list of (date, duration) tuples, how would you filter by time period and calculate summary stats (average, rolling sum)?

Can you explain the process of estimating the probability of ordering a ride using a set of assumptions? What assumptions would be required for this calculation? Furthermore, how would you determine a confidence interval for this probability?

Can you devise an algorithm that replicates the rolling of an X-sided dice with varying probabilities?

Are there any key success indicators for someone serving a role like Data Scientist?

How do you make yourself stand out?

When do you prefer mean over median? Can you walk me through an example?

What are your near term goals? How do they contribute to your long term goals?

Suppose you draw a value each day at random from a normal distribution with a mean of 0 and a standard deviation of How many days should it take on average for you to draw a value that's greater than 2?