Vector Representations of Words -- TensorFlow官網word2vec教程翻譯
本文爲Tensorflow Tutorials 詞向量教程的翻譯版本，翻譯過程即學習過程，同時也會在日後根據當前階段的理解，重新翻閱更新。 着重介紹 動機：爲何學習詞嵌入 在此教程中，我們借用Mikolov等人論文中提到的word2vec模型，此模型可將單詞映射成特定的向量，這一過程被稱爲word embedding(詞嵌入)。 着重介紹 本教程着重介紹運用TensorFlow框架構建word2v
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- 1. CS224n-02 Word Vector Representations word2vec
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相關文章
- 1. CS224n-02 Word Vector Representations word2vec
- 2. 翻譯：Distributed Representations of Words and Phrases and their Compositionality
- 3. Distributed Representations of Words and Phrases and their Compositionality--翻譯
- 4. Distributed Representations of Words and Phrases and their Compositionality翻譯與感悟
- 5. distributional similarity based representations: word2vec
- 6. Efficient Estimation of Word Representations in Vector Space
- 7. Distributed Representations of Words and Phrases and their Compositionality
- 8. (30)[ICLR13] Efficient Estimation of Word Representations in Vector Space
- 9. NLP系列：Word2Vec原始論文：Efficient Estimation of Word Representations in Vector Space
- 10. TensorFlow官方教程翻譯：TensorFlow調試器