Preguntas de entrevista de Data mining analyst
253
Preguntas de entrevista para Data Mining Analyst compartidas por los candidatosPrincipales preguntas de entrevista
Given the set a a b b a a c c b b of unknown length, write an algorithm that figures out which occurs most frequently and with the most continuous repetition.
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doesn't matter, no answer is right!
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Maintains Hashmap to store the overall frequency and longest continuous sequence. Menos
List the strings that are anagrams from a set of strings?
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Sorting the strings is not optimal because each sort is O(N log N) where N is the number of characters in each word. A more optimal solution is to create a function to encode each word as a hash table of character frequencies, which is O(N) for each word. Menos
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sort the strings and compare
How would you design a recommendation system (like amazon)?
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Use collaborate filtering to compare personal preference with others. If A and B are similar, we can recommend preferred items in B to A. Menos
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Why downvote on other answer? He/she is right. Collaborative filtering is the most common strategy for recommendation systems. You see user A buys these things and user B also bought those things but user B bought this other thing too so let's show that thing to User A. Menos
there really were none.
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they seemed ot want to hear what I had ot say about my past assignments and relevance to the opening. i think they were not impressed. Menos
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Intuited
why do you think you should be chosen for this position?
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I'm hard working, great team player, reliable, quick learner etc etc
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cuz i got a 10inch and great performer in front of the camera - porn industry
We do pre-screening on the data to remove fraud threats -- so how do we find a data sample that we can use to determine a real representation of fraud events.
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Remove screen and look at the unbiased data.
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Yes, remove prescreen and look the unbiased sample. IF the unbiased sample becomes too big, then just randomly choose 1/2, or small, for the purpose of representation of fraud events. Menos
Implement a sampling function with nominal distribution.
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I think you mean Normal distribution! If you are using R use set.seed(). You can then use rnorm() with size, mean & SD. e.g. >set.seed(123) >rnorm(100, 2, 5) Menos
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I'm the original poster, sorry for my typo. I actually mean multinomial distribution. And the advanced question was, if the probability is a skewed distribution, how would you speed up your algorithm. You can find both answer from Wikipedia. :) Menos
Tell me about your past experience in engineering.
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Provided examples from my education and work.
