January 2018
Beginner to intermediate
284 pages
8h 35m
English
Content preview from Deep Learning Essentials
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Word embeddings
The very fundamental idea of distributional similarity-based representations is that a word can be represented by the means of its neighbors. As said by J. R. Firth 1957: 11:
You shall know a word by the company it keeps
This is perhaps one of the most successful ideas of modern statistical NLP. The definition of neighbors can vary to take account of either local or larger contexts to get a more syntactic or semantic representation.
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