# hengluchang/deep-news-summarization

<https://repo.masters-masters.com/en/repos/hengluchang/deep-news-summarization>

[Home](https://repo.masters-masters.com/en) › [hengluchang](https://repo.masters-masters.com/en/owners/hengluchang) › [deep-news-summarization](https://repo.masters-masters.com/en/repos/hengluchang/deep-news-summarization)

hengluchang/deep-news-summarization has 189 stars on GitHub. Its RepoMasters card: Prototype tier. News summarization using sequence to sequence model with…

| Field | Value |
| --- | --- |
| Owner | [hengluchang](https://repo.masters-masters.com/en/owners/hengluchang) |
| Stars | 189 |
| Forks | 61 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2016 |
| Topics | tensorflow, seq2seq, tensorflow-models, news-summarization, recurrent-neural-networks, lstm, encoder-decoder, gigaword, deep-learning |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [hengluchang/deep-news-summarization](https://github.com/hengluchang/deep-news-summarization) |

## Repository

News summarization using sequence to sequence model with attention in TensorFlow.

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.