ML questions about Logistic regression model, how to deal with imbalanced data? what's the evaluation metrics I choose and the reason. How to deal with categorical data, etc.
Machine Learning Interviews
Machine Learning Interview Questions
"To get a job in machine learning, you must have the programming and mathematical knowledge to create artificial intelligence that is capable of learning new tasks without being explicitly coded. In an interview you may be asked about your experience with pertinent coding languages such as Java and C++ as well as with writing algorithms. The interview will be comprised mainly of technical questions that test your knowledge of the fundamental concepts of machine learning such as data mining and signal processing."
8,221 machine learning interview questions shared by candidates
The interview process was as below - ML Fundamentals Q&A - 10mins -- Asked Hypothesis testing, supervised and unsupervised ML models definition and overfitting and underfitting - Terraform and AWS Infrastructure Q&A - 10 mins -- How do you facilitate integration of AWS and Terraform -- How do you maintain data security in AWS according to HIPAA & GDPR -- How do you manage Data Encryption in AWS - ML System Design Q & A - 10 mins -- After a model for detecting frauds in loan sanctioning is developed, how do you handle data shifts? -- Why do data shifts take place? - Scripting - 20 mins -- Basic Python programing where I just used strings and lists to solve it. It is very easy leetcode question.
Talk about work history.
How do you track the angle between a minute hand and hour hand of a clock?
How can you solve an optimization problem with constraints?
Discuss a previous ML project
One task involved optimizing the time complexity of a linear search within a method of the class. (Binary Search)
ML coding questions, testing hands-on experience, research presentation covering past work in the field.
Just some Leekcode problems. None of them were related to the potential job.
I can't go into specifics, but I will say that the interview followed a fairly standard MLE interview process, including behavioral interviews, ML modelling, ML system design, and a practical portion involving showing how to train an actual model in an online data platform (such as databricks, colab, etc). The recruiter was very informative about the expectations for each interview
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