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1. How do you use NN to reduce dimensionality? 2. Can you model time series as a linear regression model? 3. a) Can you use resampling methods like bagging to estimate the max of a population? b) Why is bagging a variance reduction scheme? 4. Why is the use of minibatch to minimize a function computationally more efficient than any other methods? 5.Gambler's ruin problem. 6. Assume that in a time series, some data are missing. How do you handle that? A. average out the existing values. Okay, so you want to average out the existing values, but how do you define the the new time series as a single function? A. Use characteristic or indicator function.
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Data Scientist

Interviewed at Criteo

3.9★
Nov 22, 2018

1. How do you use NN to reduce dimensionality? 2. Can you model time series as a linear regression model? 3. a) Can you use resampling methods like bagging to estimate the max of a population? b) Why is bagging a variance reduction scheme? 4. Why is the use of minibatch to minimize a function computationally more efficient than any other methods? 5.Gambler's ruin problem. 6. Assume that in a time series, some data are missing. How do you handle that? A. average out the existing values. Okay, so you want to average out the existing values, but how do you define the the new time series as a single function? A. Use characteristic or indicator function.

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