For ML design it was about a recommendation system. For coding interviews - pick any leetcode-style medium level problem and implement it extremely fast. Be sure to correctly assess O-complexity for computation and memory
Learning Coordinator Interview Questions
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Height of a tree where each node can have odd number of children only
Things like "describe self-attention mechanism", "how do RNNs differ vs. transformers", "how do you use propensity scores in AB tests"
Given a string check if brackets are balanced "(())(()(()" --> no, "()(())()" --> yes Implement the power (**) operator.
In the actual interview; the first question is the closest common parents of two nodes in a binary tree given the parent node as a pointer in the node itself. And the second was the known file system path parsing problem. Both of these are leetcode
What the minimum number to add parentheses to make a string balanced.
Coding questions were medium leetcode questions and can be done with some prep. system design and ml system wasn't too hard. I couldn't do senior level on ml system design. it's more complicated than educative examples.
Do you have any questions about the team?
1. Range sum for BST 2. Balance parenthesis.
Dived really deep into my experience to identify overlap with the tools and technologies being used at Ground News.
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