kjw0612/awesome-rnn resource
Recurrent Neural Network - A curated list of resources dedicated to RNN observed · 2026-08-28
Health v2 · maintenance only
23/100
- Activity 0
- Release rhythm 8
- Longevity 100
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 4097
- days_rel: n/a
- days_push: 1672
- n_releases_24m: 0
Adoption not part of the score
6210 stars · 1419 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
A curated list of resources on recurrent neural networks, including code, papers, lectures, books, and application examples across NLP, computer vision, and multimodal tasks. It is an awesome-list style reference rather than software.
Use cases
- find papers and tutorials on RNNs and LSTMs
- learn about sequence-to-sequence and language modeling resources
- discover RNN code examples and datasets
- explore RNN applications in translation, speech, and image captioning
- find surveys and architecture variants of recurrent networks
When to choose
- you want a broad curated index of RNN learning materials
- you are researching classic RNN literature and architectures
When to avoid
- you need actively maintained or up-to-date resources
- you want runnable software rather than a link list
- you need modern transformer-era content
Facets
learning-resource · maturity abandoned
documentation deep-learning machine-learning computer-vision tutorials cross-platform awesome-list recurrent-neural-networks rnn lstm curated-list papers tutorials natural-language-processing
1 source
- readme: https://github.com/kjw0612/awesome-rnn · fetched 2026-08-28 · 6ae1cbc71466
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| kjw0612/awesome-rnn | main | 23 |
For agents
markdown · JSON · MCP: product_card(name="kjw0612/awesome-rnn")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem