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What does log loss indicate in predictive modeling?

Suppose we have a dataset of (date, duration) tuples. How would you filter by a specific time period and then generate summary statistics, including the average duration and rolling sum, for each date within that time period?

Assuming you are randomly drawing values each day from a normally distributed variable with a mean of 0 and a standard deviation of 1, what is the expected number of days it would take for you to draw a value greater than 2?

What are the benefits and drawbacks of incorporating decision trees into a machine learning model?

Give a brief description of your work experience

How would you explain the difference between linear and logistic regression to a novice?

Could you walk us through the benefits of using LSTM in machine learning and how it differs from other deep learning models? Additionally, can you share any experiences you've had working with LSTM?

Write a code to generate independent and identically distributed (i.i.d.) draws from a given distribution X given that we only have access to a random number generator.

How do you draft a SQL query to extract rows where the name field starts with 'H'?

In the role of OpenDoor Data Scientist, what would be the biggest challenge you think you would face?