# apachecn/Interview

Interview = 简历指南 + 算法题 + 八股文 + 源码分析

Repository: https://github.com/apachecn/Interview
Canonical: https://ross.abutalabs.com/products/apachecn-interview
Homepage: https://interview.apachecn.org
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Topics: python, kaggle, machine-learning, leetcode, interview
Last push: 2023-10-20T08:12:51+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3246, "days_push": 1048, "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 8960, forks 2144 (observed 2026-08-28T04:10:26.511605+00:00)

## What it is
A Chinese-language IT interview knowledge base maintained by ApacheCN, covering resume guidance, algorithm problems (LeetCode-style), common interview questions, source code analysis, and machine learning project walkthroughs. It includes detailed Kaggle competition tutorials (Digit Recognizer, Titanic, House Prices, NLP sentiment analysis) with full Python code and methodology.

## Use cases
- prepare for software engineering interviews
- study leetcode algorithm problems with explanations
- learn how to approach kaggle competitions step by step
- review machine learning interview questions and project workflow
- get resume and career guidance for IT jobs
- practice feature engineering and model ensembling on classic datasets
- find Chinese-language study material for data science interviews

## When to choose
- you are preparing for IT or ML job interviews and prefer Chinese-language material
- you want guided, code-complete walkthroughs of beginner Kaggle competitions
- you need a consolidated collection of algorithms, interview questions, and resume tips

## When to avoid
- you need up-to-date interview content - the latest release is from 2023 and updates appear infrequent
- you need English-language interview preparation
- you want an interactive coding platform rather than a static knowledge base
- you require production-grade ML tooling rather than study notes

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, data-science, documentation
- domain: tutorials, machine-learning, education, developer-tools
- platform: python, cross-platform
- tags: interview-preparation, leetcode, kaggle, chinese, resume-guide, study-notes, apachecn

## Member repositories
- apachecn/Interview (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:26.511605+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 2026-08-29T17:24:27.757184+00:00, confidence not recorded.
  - readme: https://github.com/apachecn/Interview (fetched 2026-08-28T04:10:26.511605+00:00, sha 16644ddb382c)
  - homepage: https://interview.apachecn.org (fetched 2026-08-29T08:24:45.708662+00:00, sha c66997a8a8a0)
  - site_page: https://interview.apachecn.org/Kaggle/kaggle-quickstart (fetched 2026-08-29T08:24:45.711570+00:00, sha dc0bcc20879c)
  - site_page: https://interview.apachecn.org/Kaggle/competitions/getting-started/digit-recognizer (fetched 2026-08-29T08:24:45.729441+00:00, sha 95c7baf9144d)
  - site_page: https://interview.apachecn.org/Kaggle/competitions/getting-started/titanic (fetched 2026-08-29T08:24:45.732252+00:00, sha 9806ed246f21)
  - site_page: https://interview.apachecn.org/Kaggle/competitions/getting-started/house-price (fetched 2026-08-29T08:24:45.734412+00:00, sha 3ec9c0264312)
  - site_page: https://interview.apachecn.org/Kaggle/competitions/getting-started/word2vec-nlp-tutorial (fetched 2026-08-29T08:24:45.737184+00:00, sha f3237bc0bc6a)
  - site_page: https://www.apachecn.org/about (fetched 2026-08-29T08:24:45.740061+00:00, sha 211b768594dc)
- Data as of 2026-08-30T08:39:29.467469+00:00.