基於PyTorch實現Seq2Seq + Attention的英漢Neural Machine Translation
NMT(Neural Machine Translation)基於神經網絡的機器翻譯模型效果愈來愈好，還記得大學時代Google翻譯效果仍是差強人意，近些年來使用NMT後已基本能知足非特殊需求了。目前NMT的主流模型是採用Seq2Seq + Attention架構，本文基於PyTorch實現一個小型的英文到中文的翻譯系統。git 一、數據集 數據集及所有代碼下載連接：百度網盤，提取碼：sauzgi
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相關文章
- 1. lecture8 - Machine Translation Seq2Seq and Attention
- 2. CS224n-Lecture8-Machine Translation, Seq2Seq and Attention
- 3. 【cs224n-7】Machine Translation, Seq2Seq and Attention
- 4. 【CS224n】Neural Machine Translation with Seq2Seq
- 5. Seq2Seq(Attention)的PyTorch實現
- 6. cs224筆記：Lecture 8 Machine Translation, Seq2Seq and Attention
- 7. Paper：Effective Approaches to Attention-based Neural Machine Translation
- 8. Fine-Grained Attention Mechanism for Neural Machine Translation
- 9. [EMNLP2015]Effective Approaches to Attention-based Neural Machine Translation
- 10. 論文筆記(Attention 2)-----Effective Approaches to Attention-based Neural Machine Translation