# DSKSD/RNN-for-Joint-NLU

<https://repo.masters-masters.com/en/repos/DSKSD/RNN-for-Joint-NLU>

[Home](https://repo.masters-masters.com/en) › [DSKSD](https://repo.masters-masters.com/en/owners/DSKSD) › [RNN-for-Joint-NLU](https://repo.masters-masters.com/en/repos/DSKSD/RNN-for-Joint-NLU)

DSKSD/RNN-for-Joint-NLU has 198 stars on GitHub. Its RepoMasters card: Prototype tier. Pytorch implementation of "Attention-Based Recurrent Neural Network…

| Field | Value |
| --- | --- |
| Owner | [DSKSD](https://repo.masters-masters.com/en/owners/DSKSD) |
| Stars | 198 |
| Forks | 49 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | None |
| Created | 2017 |
| Topics | intent, slot-filling, task-oriented-dialogue, nlu, rnn, lstm, attention, encoder-decoder |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [DSKSD/RNN-for-Joint-NLU](https://github.com/DSKSD/RNN-for-Joint-NLU) |

## Repository

Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.