deep-learning
Word embeddings
taught
Taught in
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word2vec: skip-gram and CBOW
Deep Learning / Neural Networks
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Tokens and embeddings recalled
Wiring Language Models
Requires
- one-hot-limitations required
Required by
- GloVe and co-occurrence statistics required
- Sentence and document embeddings recommended
- Similarity and analogy in embedding space required
- word2vec (skip-gram and CBOW) required
Local knowledge map
Local knowledge map
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Solid arrows are required prerequisites; dashed are recommended or helpful. Lower rows are more foundational. Click any box to jump to that concept.