Dynamic programming/backward induction on a multi-stage decision making problem
Data Scientist Data Science Department Interview Questions
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Work through problems on the hackerrank site, it's good preparation
-Resume related questions - Process of building a predictive model
There were some specific stats questions that I wished I had answered better.
what is ensemble Learning Algorithms kinds ?
What metric would you show small businesses if you were trying to have them sign up for Facebook Ads
Tell me about a time when you received constructive criticism and how you handled it.
We have two types of reviewers: careful reviewer (80% of reviewers) and lazy reviewers (20% of reviewers). Careful reviewers rate a post positive 60% of time and negative 40% of time). Lazy reviewers however rate a post positive 100% of time. A) what is the probability that a random ad is reviewed positively? B) If an ad gets a negative review, what is the probability that it's reviewed by a lazy reviewer? C) If 3 ads are reviewed positively in a row, what is the probability that they are reviewed by a lazy reviewer? D) Some as above with n positively reviewed ads in a row. What happens when n goes to infinity? E) If we have very few labeled data, how can we build a model to distinguish between careful and lazy reviewers?
Take-home exercise on a typical analysis case and was asked to provide solution and thought process in a week.
If there's a new feature that attracts more pop stars to use it, how do you evaluate whether this feature is successful or not?
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