The questions ranged from basic topics like bias vs. variance trade-offs to advanced topics like LLMs and self-supervised learning. Usually, they will give you a hypothetical scenario and ask you to solve the problem using ML. Based on your answer, you are asked subsequent questions.
Describe the flow of a project that you have worked on.
They asked me about some ML cases where we talked about monitoring, scalibility etc. Usual system design stuff with ML add-ons.
Questions regarding ambitions and goals. Technical questions involved a good knowledge of machine learning tools, particularly neural nets and dataset representations
What are the algorithms used in machine learning
Questions on logic and basic probability, describe a machine learning algorithm from scratch.
Write a function to find connected components of an undirected graph.
what are t test, z test and F test?
Q: Introduce yourself a little bit.
Implement a python decorator to cache recursive function results.
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