# msgi/nlp-journey

Documents, papers and codes related to  Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc.

Repository: https://github.com/msgi/nlp-journey
Canonical: https://ross.abutalabs.com/products/nlp-journey
Homepage: https://github.com/msgi/nlp-journey
Language: Python
License: Apache-2.0
License Family: permissive
Topics: deep-learning, paper
Last push: 2026-02-11T17:42:41+00:00

## Health v2 (maintenance only)
Score: 62/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 67, release rhythm 35, longevity 100
- inputs: {"age_days": 2690, "days_push": 203, "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 1629, forks 375 (observed 2026-08-28T04:05:13.768582+00:00)

## What it is
A curated collection of documents, papers, and Python code covering core Natural Language Processing topics such as topic models, word embeddings, NER, text classification, generation, similarity, and machine translation. It also includes book references, Transformer-era paper lists, and an LLM chat tutorial.

## Use cases
- learn natural language processing from papers and code
- find reading lists for transformers like BERT and GPT
- study word embeddings and topic models with example implementations
- get started with LLM chat applications
- review classic deep learning papers for NLP
- prepare for NLP interviews or coursework

## When to choose
- you want a curated paper and code collection for learning NLP
- you need references spanning classic models to Transformer-era research
- you prefer learning by reading papers alongside Python implementations

## When to avoid
- you need a production-ready NLP library or framework
- you want maintained, tested tooling rather than study material
- you need comprehensive tutorials rather than a paper index

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: nlp, machine-learning, deep-learning
- domain: deep-learning, tutorials, machine-learning
- platform: python, cross-platform
- tags: papers, curated-list, word-embeddings, text-classification, machine-translation, topic-modeling, transformers, study-notes, natural-language-processing

## Member repositories
- msgi/nlp-journey (main) score 62

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:13.768582+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 2026-08-30T03:48:17.564754+00:00, confidence not recorded.
  - readme: https://github.com/msgi/nlp-journey (fetched 2026-08-28T04:05:13.768582+00:00, sha bddb6feecf3c)
  - homepage: https://github.com/msgi/nlp-journey (fetched 2026-08-29T11:20:52.633807+00:00, sha f16724d6cb8d)
- Data as of 2026-08-30T08:39:29.467469+00:00.