Moderate level questions on the decisions to apply a particular ML algorithm on a dataset, (What they're looking for is a reasoning that factors in everything like inference time, results examinability(XAI or SHAP) and not just what algorithm will be the most accurate on a dataset. )
This question was asked in tech round 2. Buy and sell stocks at most 2 times and get the max profit.
Binary Search Algorithm and Big O for it
BFS on a binary tree
Explain the thought processes for previous OA question
Can you describe your role in your current project?
How to revert a single linked list? I solved, but with a mistake for the first time. After rewriting I had little time, so interview ended. That was my fault, I guess.
Imagine a random distribution of water droplets spread across the whiteboard, design an algorithm to create the maximal enclosed area by connecting the water droplets with lines.
Design / implementation considerations while implementing a service talking to database which is deployed on Premise Vs Azure.
If an application team wants servers and storage just to test, what do you tell them?
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