Gd questions/topics: ANN vs CNN, Transformers, ViT, data processing, drawbacks.
Machine Learning Research Engineer Interview Questions
1,879 machine learning research engineer interview questions shared by candidates
How do you declare a variable, in a language of your choice. Describe what cloud engineering is.
Explain over- and under-fitting and how to combat them?
Some simple algorithm problems (can't remember exactly what they were), solved by a for loop or a nested for loop. Questions about their time and space complexity. Basic theoretical ML questions (explain and give examples of regularization, how to do classification on imbalanced data, etc).
The online assessment has four sections: SQL Queries: Writing SQL queries. MCQ for Data Science: Multiple-choice questions related to data science. MCQ for Statistics & Probability: Multiple-choice questions on statistical concepts and probability. Python Coding: Writing Python code to solve a coding problem. The Technical Interview stage involves an interview with a Karat interviewer. This interview is not a typical discussion about the work you've done; rather, it's more like an extension of the online assessment. The interviewer asks questions similar to queries, poses statistics questions (e.g., about p-values and appropriate distributions for different scenarios), and requires you to solve a Python coding question. During this stage, you are allowed to use Google, but it's crucial to communicate openly about what you are looking up. Copy-pasting from sources like ChatGPT is discouraged, and the interview is conducted via video.
Do you use Fairtiq app? What do you like or don't like about the app? Have you read the job description? Do you meet the requirements specified there?
Most are the projects in my resume
What are different techniques used to split datasets for training models?
Can you explain the bias variance tradeoff?
Questions on Deep Learning models related to publications
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