# NLP-LOVE/Introduction-NLP

HanLP作者的新书《自然语言处理入门》详细笔记！业界良心之作，书中不是枯燥无味的公式罗列，而是用白话阐述的通俗易懂的算法模型。从基本概念出发，逐步介绍中文分词、词性标注、命名实体识别、信息抽取、文本聚类、文本分类、句法分析这几个热门问题的算法原理与工程实现。

Repository: https://github.com/NLP-LOVE/Introduction-NLP
Canonical: https://ross.abutalabs.com/products/introduction-nlp
Homepage: http://era.dx3906.info
Language: Python
License: Apache-2.0
License Family: permissive
Topics: nlp, mechine-learing, deep-learning, ai
Last push: 2026-01-09T15:18:42+00:00

## Health v2 (maintenance only)
Score: 60/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 61, release rhythm 35, longevity 100
- inputs: {"age_days": 2403, "days_push": 236, "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 2267, forks 544 (observed 2026-08-28T04:06:32.798087+00:00)

## What it is
Detailed study notes for the book 'Introduction to Natural Language Processing' by the author of HanLP, covering Chinese word segmentation, POS tagging, NER, information extraction, text clustering/classification, and dependency parsing. It is a tutorial-style repository of chapter-by-chapter notes with algorithm explanations and engineering implementations in Python.

## Use cases
- learn chinese word segmentation algorithms
- understand hidden markov models for sequence labeling
- study named entity recognition from basics
- learn text classification and clustering
- understand dependency parsing
- get started with nlp in chinese
- find notes on conditional random fields

## When to choose
- you want beginner-friendly Chinese-language explanations of classical NLP algorithms
- you are reading the book 'Introduction to NLP' and want supplementary notes
- you want to learn Chinese word segmentation, tagging, and parsing fundamentals

## When to avoid
- you need a production NLP library rather than study notes
- you want modern transformer/LLM-focused tutorials
- you need English-language learning material

## Facets
- artifact type: learning-resource
- maturity: active
- function: nlp, machine-learning, deep-learning
- domain: tutorials, machine-learning
- platform: python
- tags: chinese-nlp, book-notes, hanlp, text-segmentation, sequence-labeling, text-classification, natural-language-processing

## Member repositories
- NLP-LOVE/Introduction-NLP (main) score 60

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:32.798087+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 2026-08-30T02:42:06.121516+00:00, confidence not recorded.
  - readme: https://github.com/NLP-LOVE/Introduction-NLP (fetched 2026-08-28T04:06:32.798087+00:00, sha 2ca0a718833b)
  - homepage: http://era.dx3906.info (fetched 2026-08-29T10:22:29.147841+00:00, sha e720b92c0aa8)
- Data as of 2026-08-30T08:39:29.467469+00:00.