1. Machine Learning Case Study: given a prompt, talk through how to formulate a ML problem, staring from what data to use, how to clean those data, preprocessing, ML modeling, validation and evaluation 2. General ML question in details: mathematical derivatives, algorithms comparisons, what methods to use for XXX data or problem, etc 3. Behavior questions: why chase, what to do if meet some stakeholders that does not understand ML , etc.
what is CTE and stored procedure?
Why you want to work at Gallagher?
skill reviews and personality quiz.
How does a bank work
What do you learn from your failure?
What do you need if some one want a finance from our company?
Parameters to be considered before providing Auto loan? Model feature selection? Logistic Regression?
Parameters to be considered before providing Auto loans? Model feature selection?
How to reduce the variables?
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