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khangich/machine-learning-interview resource

Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io. observed · 2026-08-28

github.com/khangich/machine-learning-interview observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 2213
  • days_rel: n/a
  • days_push: 1098
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

12795 stars · 2045 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A curated study guide and knowledge base for machine learning interviews at top tech companies, covering ML system design, deep learning concepts, and coding questions. It accompanies the author's books and courses, drawing on interview experience from Google, LinkedIn, Snap, and other companies.

Use cases

  • prepare for a machine learning interview at FAANG
  • study ML system design questions like YouTube recommendations or feed ranking
  • find a minimum viable study plan for ML interviews
  • practice leetcode-style questions for ML roles
  • learn how recommendation and ranking systems are designed
  • review common machine learning interview questions

When to choose

  • you are interviewing for ML engineer or data scientist roles at large tech companies
  • you want structured, experience-based guidance on ML system design interviews
  • you need a free, community-vetted study plan with real interview examples

When to avoid

  • you need a software library or tool rather than study material
  • you are looking for general software engineering interview prep without an ML focus
  • you need formally licensed or maintained educational content for commercial training use

Facets

learning-resource · maturity maintenance

machine-learning deep-learning developer-tools machine-learning education tutorials artificial-intelligence cross-platform interview-preparation leetcode system-design faang study-guide career

1 source

Member repositories

RepositoryRoleHealth v2
khangich/machine-learning-interviewmain32

For agents

markdown · JSON · MCP: product_card(name="khangich/machine-learning-interview")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem