# songyingxin/NLPer-Interview

该仓库主要记录 NLP 算法工程师相关的面试题

Repository: https://github.com/songyingxin/NLPer-Interview
Canonical: https://ross.abutalabs.com/products/nlper-interview
License Family: other
Last push: 2022-04-12T13:11:22+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": 2603, "days_push": 1604, "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 2757, forks 504 (observed 2026-08-28T04:07:18.348414+00:00)

## What it is
A curated collection of study notes and interview questions for NLP algorithm engineer positions, covering Python/C++, math, machine learning, deep learning, and NLP topics like word embeddings and pretrained language models. It is a Markdown-based knowledge repository intended to help candidates prepare for technical interviews.

## Use cases
- prepare for an NLP algorithm engineer interview
- review machine learning fundamentals like SVM and decision trees
- study deep learning basics such as CNN, RNN, and gradient problems
- revise word embedding concepts like Word2Vec, GloVe, and FastText
- understand pretrained language models like BERT
- brush up on Python and C++ interview questions
- review probability, linear algebra, and information theory for interviews

## When to choose
- you are preparing for NLP or machine learning engineer interviews and want organized topic-based notes
- you want a free Chinese-language study guide covering math, ML, DL, and NLP fundamentals
- you need a checklist of common interview topics to find your knowledge gaps

## When to avoid
- you need a runnable software library or tool rather than study notes
- you want up-to-date content covering recent LLM-era topics, as the repo was last updated in 2022
- you need English-language interview preparation materials

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: nlp, machine-learning, deep-learning
- domain: machine-learning, tutorials
- platform: cross-platform
- tags: interview-preparation, study-notes, chinese, nlp-interview, algorithm-engineer, natural-language-processing

## Member repositories
- songyingxin/NLPer-Interview (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:18.348414+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 2026-08-30T08:18:49.248182+00:00, confidence not recorded.
  - readme: https://github.com/songyingxin/NLPer-Interview (fetched 2026-08-28T04:07:18.348414+00:00, sha 93bc4e728067)
- Data as of 2026-08-30T08:39:29.467469+00:00.