# boost-devs/ai-tech-interview

👩‍💻👨‍💻 AI 엔지니어 기술 면접 스터디 (⭐️ 2k+)

Repository: https://github.com/boost-devs/ai-tech-interview
Canonical: https://ross.abutalabs.com/products/ai-tech-interview
Homepage: https://boostdevs.gitbook.io/ai-tech-interview/
License: MIT
License Family: permissive
Topics: tech-interview, study, artificial-intelligence, python, computer-science
Last push: 2026-03-17T15:34:11+00:00

## Health v2 (maintenance only)
Score: 65/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 72, release rhythm 35, longevity 100
- inputs: {"age_days": 1970, "days_push": 169, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2357, forks 511 (observed 2026-08-28T04:06:40.705589+00:00)

## What it is
A community-maintained Korean-language study repository of AI engineer technical interview questions with curated answers, covering statistics, machine learning, deep learning, and computer science fundamentals. It is also available as a GitBook site and a Streamlit practice app.

## Use cases
- prepare for an AI engineer technical interview
- study machine learning interview questions with answers
- review statistics and math fundamentals before interviews
- practice deep learning interview questions
- find a curated question bank for AI/ML job interviews

## When to choose
- you are preparing for AI/ML engineer interviews and want a broad question bank with community answers
- you prefer structured study material organized by topic
- you read Korean and want interview prep in that language

## When to avoid
- you need a hands-on coding course or tutorials with runnable code
- you need up-to-date coverage of very recent LLM topics
- you need English-only material

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation
- domain: artificial-intelligence, machine-learning, tutorials, education
- platform: -
- tags: tech-interview, study-guide, interview-questions, korean, statistics, deep-learning, web-server

## Member repositories
- boost-devs/ai-tech-interview (main) score 65

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:40.705589+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 2026-08-30T02:36:16.464510+00:00, confidence not recorded.
  - readme: https://github.com/boost-devs/ai-tech-interview (fetched 2026-08-28T04:06:40.705589+00:00, sha 3678788ed00d)
- Data as of 2026-08-30T08:39:29.467469+00:00.