Question: How would you approach building a machine learning model to predict customer churn? Answer: I outlined steps for data preprocessing, feature engineering, model selection, hyperparameter tuning, and evaluating metrics like precision and recall to ensure the model accurately identifies churn patterns.
Initial call, take-home coding interview, phone call to review work.
Past experience, describe a project, very detailed questions to technical & business implementation and impact; take-home: Given a dataset of payments: Define a problem, solve the problem
Typical background / personal questions. Everyone was friendly / professional. They get back to you for the interview results with feedbacks which is rare. Seems like a great company to work at.
They were standard for biotech.
The recruiter scheduled a phone call, but never called!
Regression, Clustering, Classification, Computer Vision, NLP concepts
Basic fundamentals and ppt about project
Discuss why you did your project the way you did.
What is Linear regression ?
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