# fastai/course-nlp

A Code-First Introduction to NLP course

Repository: https://github.com/fastai/course-nlp
Canonical: https://ross.abutalabs.com/products/course-nlp
Homepage: https://www.fast.ai/2019/07/08/fastai-nlp/
Language: Jupyter Notebook
License Family: other
Topics: nlp, machine-learning, data-science, python
Last push: 2023-03-22T15:41:27+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": 2668, "days_push": 1260, "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 3488, forks 1454 (observed 2026-08-28T04:08:07.120647+00:00)

## What it is
A code-first university course introducing natural language processing through Jupyter notebooks in Python, covering topic modeling, sentiment classification, language modeling, and translation with RNNs and Transformers. It uses libraries such as sklearn, nltk, pytorch, and fastai and includes lecture videos.

## Use cases
- learn nlp from scratch with code
- understand transformers and attention
- learn topic modeling with nmf and svd
- build sentiment classifiers with naive bayes and logistic regression
- learn language modeling and transfer learning
- study bias and ethics in nlp

## When to choose
- you want a hands-on, notebook-driven introduction to NLP
- you prefer a top-down teaching style with working code
- you want to learn classical NLP through deep learning approaches

## When to avoid
- you need production-ready NLP software
- you want an actively updated course with the latest LLM content
- you need a licensed or formally supported project

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: nlp, machine-learning, data-science
- domain: machine-learning, data-science, tutorials
- platform: python, jvm
- tags: jupyter-notebooks, course, fastai, pytorch, nltk, education, natural-language-processing

## Member repositories
- fastai/course-nlp (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:07.120647+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 2026-08-29T18:36:06.413887+00:00, confidence not recorded.
  - readme: https://github.com/fastai/course-nlp (fetched 2026-08-28T04:08:07.120647+00:00, sha 13d5772f92bf)
  - homepage: https://www.fast.ai/2019/07/08/fastai-nlp/ (fetched 2026-08-29T09:30:09.650593+00:00, sha 259fc07dcea4)
- Data as of 2026-08-30T08:39:29.467469+00:00.