# andrewekhalel/MLQuestions

Machine Learning and Computer Vision Engineer - Technical Interview Questions

Repository: https://github.com/andrewekhalel/MLQuestions
Canonical: https://ross.abutalabs.com/products/mlquestions
Language: Python
License Family: other
Topics: computer-vision-interview-questions, data-science-interview, data-science-interview-questions, data-science-interviews, deep-learning-interview, deep-learning-interview-questions, machine-learning-interview, machine-learning-interview-questions, ml-interview, ml-interview-prep, ml-interviews, nlp-interview-questions
Last push: 2026-08-25T13:04:25+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 2821, "days_push": 8, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4791, forks 777 (observed 2026-08-28T04:08:59.885221+00:00)

## What it is
A curated collection of 67 machine learning interview questions with answers, covering ML fundamentals, deep learning, computer vision, NLP, statistics, and coding. It is community-maintained since 2018 and also available as a browsable website.

## Use cases
- prepare for a machine learning engineer interview
- study deep learning interview questions
- review computer vision interview questions and answers
- practice data science interview questions
- brush up on NLP interview questions
- review statistics and coding questions before an ML interview

## When to choose
- you are preparing for ML, data science, deep learning, computer vision, or NLP engineering interviews
- you want concise question-and-answer style review material
- you prefer a free, community-maintained question bank browsable by topic

## When to avoid
- you need structured courses or hands-on exercises rather than Q&A lists
- you need up-to-date coverage of very recent techniques, as answers link to older articles
- you need a formal license for redistribution, since the repository has no license

## Facets
- artifact type: learning-resource
- maturity: active
- function: nlp, computer-vision, machine-learning
- domain: machine-learning, tutorials, education, computer-vision, data-science
- platform: -
- tags: interview-questions, interview-preparation, machine-learning-interview, study-guide, q-and-a, natural-language-processing, web-server

## Member repositories
- andrewekhalel/MLQuestions (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:59.885221+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:18:41.279841+00:00, confidence not recorded.
  - readme: https://github.com/andrewekhalel/MLQuestions (fetched 2026-08-28T04:08:59.885221+00:00, sha d94ad5b40eac)
- Data as of 2026-08-30T08:39:29.467469+00:00.