# makcedward/nlp

:memo: This repository recorded my NLP journey.

Repository: https://github.com/makcedward/nlp
Canonical: https://ross.abutalabs.com/products/makcedward-nlp
Homepage: https://makcedward.github.io/
Language: Python
License Family: other
Topics: nlp, deep-learning, machine-learning, data-science, ai
Last push: 2020-08-29T04:04:59+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3029, "days_push": 2195, "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 1082, forks 318 (observed 2026-08-28T04:03:30.940968+00:00)

## What it is
A tutorial repository documenting the author's NLP learning journey, with notebooks and articles covering text preprocessing, tokenization, and data augmentation. It accompanies the nlpaug library and links to Medium articles on NLP techniques.

## Use cases
- learn nlp fundamentals like tokenization and lemmatization
- understand data augmentation for text models
- find tutorials on text preprocessing pipelines
- study adversarial attacks on NLP models
- get started with subword tokenization
- learn back translation for text augmentation

## When to choose
- you want guided tutorials with runnable notebooks for NLP concepts
- you are learning text preprocessing and augmentation techniques
- you prefer article-plus-code style learning resources

## When to avoid
- you need a production-ready NLP library
- you need maintained, licensed software for a project
- you need comprehensive coverage of modern LLM techniques

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: nlp, machine-learning, deep-learning
- domain: machine-learning, tutorials
- platform: python
- tags: notebooks, data-augmentation, text-preprocessing, educational, natural-language-processing

## Member repositories
- makcedward/nlp (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:30.940968+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 2026-08-30T06:51:16.751685+00:00, confidence not recorded.
  - readme: https://github.com/makcedward/nlp (fetched 2026-08-28T04:03:30.940968+00:00, sha 8fe0777c34f1)
  - homepage: https://makcedward.github.io/ (fetched 2026-08-29T12:53:41.694108+00:00, sha b8806abb5f24)
- Data as of 2026-08-30T08:39:29.467469+00:00.