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Machine learning engineer Interview Questions

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standard ML and software engineering questions.

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There's a lot of elements to typically cover in these questions, clarifications, scoping, making sure you're answering the actual question the interviewer is looking for you to answer, etc. Could be worth doing a mock interview with one of the Prepfully OakNorth Machine Learning Engineer experts... they've worked in the role so they clearly know how to get through the interview. prepfully.com/practice-interviews

Given a Jupyter notebook with code to load a classifier and images, there is a bug on inference. Find it and explain.

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What is machine learning used in our day to day lives?

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General ML questions: explain how algorithm x works, how would you generalise this approach to a production problem, what considerations should be taken in terms of training properly.

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Why use F1 over accuracy?

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Given some ML-related source file, explain it. What does it do? How does it fit a project?

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Coding questions were similar to leetcode and other competitive programming

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Two classic "leetcode" style questions, one involving a binary search and the other dynamic programming. Prepare using the classic resources available online and you will be fine.

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They are really interested (understandably) about python competence and have a series of questions that you can only answer if you know python well enough.

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why do you want to get a job in data?

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