# lyeoni/nlp-tutorial

A list of NLP(Natural Language Processing) tutorials

Repository: https://github.com/lyeoni/nlp-tutorial
Canonical: https://ross.abutalabs.com/products/lyeoni-nlp-tutorial
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: nlp, natural-language-processing, nlp-tutorial, neural-machine-translation, text-classification, sentiment-classification
Last push: 2020-04-01T11:35:17+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": 2865, "days_push": 2345, "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 1375, forks 262 (observed 2026-08-28T04:04:33.088190+00:00)

## What it is
A collection of Jupyter Notebook tutorials on natural language processing built with PyTorch (and one Keras example). It covers text classification, sentiment analysis, question-answer matching, and neural machine translation with step-by-step annotated implementations.

## Use cases
- learn nlp with pytorch
- text classification tutorial
- sentiment analysis example code
- neural machine translation seq2seq tutorial
- transformer text classification walkthrough
- korean nlp text classification example

## When to choose
- you want annotated, runnable notebooks for common NLP tasks
- you are learning PyTorch through NLP examples
- you need reference implementations of CBoW, LSTM, TextCNN, or seq2seq models

## When to avoid
- you need a production-ready NLP library
- you require up-to-date code, as the project has not been updated since 2020
- you want tutorials on modern large language models

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: nlp, machine-learning
- domain: machine-learning, tutorials
- platform: python
- tags: pytorch, jupyter-notebook, text-classification, sentiment-analysis, neural-machine-translation, seq2seq, transformer, natural-language-processing

## Member repositories
- lyeoni/nlp-tutorial (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:33.088190+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 2026-08-30T04:40:34.608362+00:00, confidence not recorded.
  - readme: https://github.com/lyeoni/nlp-tutorial (fetched 2026-08-28T04:04:33.088190+00:00, sha dbf7770335b8)
- Data as of 2026-08-30T08:39:29.467469+00:00.