Comments (2)
While it is true that the Word2vec model is not deep in and of itself, the word vectors derived from it act as the building blocks of various deep learning models (especially those dealing with natural language). Besides, the understanding of the variations of word2vec algorithms (GloVe, fastText etc.) and their advantages over each other is not only pedagogical, but also aids in the choice of pretrained word embeddings.
Further, since this is a roadmap to deep learning and not merely a collection of research papers in deep learning, word2vec's presence in the roadmap is justified.
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@saurabhmathur96 Sure, I agree. =D
Maybe just making a note of this fact on the home page would be good, but it's your call.
I'll close this then.
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Related Issues (20)
- Why the same model performs better in 5-way 5-shot than 5-way 1-shot ?
- paper [52] link broken HOT 1
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- Missing ' on line 87
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