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.
Machine Learning Internship Interview Questions
8,221 machine learning internship interview questions shared by candidates
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
They asked me to assess the separability of some accelerometer data for use in an activity detection algorithm
- what would your colleagues say about you? - Talk about a project/work you're most proud of.
Explanation of self-attention in transformers.
Have you run into any problems?
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