Learning Technology Interview Questions

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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).
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Machine Learning Engineer

Interviewed at Proxify

4.1
Nov 9, 2023

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.
Dec 11, 2023

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.

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