Questions on my project of speech emotion recognition. The interviewer was mostly interested in how i would scale this model for real world application.
Applied Scientist Interview Questions
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What is the bayesian prior that induces the Ridge (L^2) regularized regression?
Describe a time when your colleague has confronted you about work. Which is the best technical project you have worked upon?
I was asked some basic ML questions and a coding question (easy on Leetcode).
ML questions, Computer Vision Questions, Coding focus on Data Structures with thoughts on dynamic programming.
- What is the motivation to apply for this position? - What is the most difficult point in your research?
Each interviewer asked 2 LP questions.
First round: - phone/video interview with one person. - Asked the typical DS interview questions (overfitting/cross validation), talked about my ML experiences. - Asked a basic coding question: given an animal, print out the noise it makes. Basic things like polymorphism/inheritance, briefly touched on string similarity Second round in person (5 interviews): - Lots of leadership principle/behavioral questions - One coding interview. Given a database of book titles and number of copies sold, how do you identify the top N most-sold books. Basic algorithm/data structures of things like priority queues/heaps, space-time complexity analysis, live-coding. Even if you miss the correct data structure, they provide some hints along the way so you can complete the problem - Multiple DS interviews, from things like typical DS interview questions and your ML experience, to an applied DS question (deduplicating transactions, how would you solve this problem, how would you build/train/score a model, how would you scale it)
How did the last product you worked on help the customer?
Write down the pseudo-code of Kmeans Detailed questions of random forest methods
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