Round 2: Many questions and cross questions on your approach to the case study - why would you choose this data, what else could you do. Other what-if scenarios on this. In modelling, fundamental questions of how some model works - not superficial level answers but demanded thorough answers.
what is random forest? why is naive bayes good?
write recursive functions
What are disadvantages of MAPE
First interview - Technical questions about the solution proposed (why random forests, difference between other algos, etc)
Write a function to multiply all other terms in the input together. Ex c(1, 2, 3, 4,) outputs c(24, 12, 8, 6)
Explain the data requirements for yield prediction?
Why PwC?
How did you do feature selection?
How do you handle multicollinearity?
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