ML questions with mathematical deductions, including MLE. Technical discussions about the Kite-specific prediction tasks.
Learning Technology Interview Questions
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The technical phone screen was more oriented toward software engineering and pretty challenging but that made it really interesting.
Estimate multivariate gaussian population parameters from data.
It was scenario questions and questions based on your work experience.
Find overlapping events in a calendar
The first call - general HR questions about the company, my expertise and motivation. The technical interview - asked about my previous projects, how I approached various problems, theoretical ML related questions (e.g. what is the difference between decision tree and random forest)
In Technical interview of 30-50 minutes, -> simple basics of C like (values and referencing,memory management,stack and heap memory) ->puzzle of probability or simple geeksforgeeks puzzles(they don't see if you answer correct or not, but check your cognitive skills) ->Why the complexity of mergeSort is O(n log(n)). ->Database Questions(they check your logic not queries). ->Problem Solving Question( Again logic is important). -> Machine Learning Logic Check like Predict if maid will come tomorrow or not. Tell me which meaning attributes in data would be required to predict so. (I told 7-8 like weather, way of speaking of maid daily, her family functions and more). As you can see Interview questions were good. They are checking if you can think or not. Also other basic interview questions were asked.
They asked asked about job experience, nothing out of the ordinary.
Pruning of decision tree
What i do at my work on daily basis in the last company
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