Word Embedding explained in one slide

How artificial intelligence understand semantics

Posted by Francesco Gadaleta on October 30, 2016

Word embeddings is one of the most powerful concepts of deep learning applied to Natural Language Processing. Any word of a dictionary (the set of words recognized for the specific task) is basically transformed into a numeric vector of a certain number of dimensions. All the rest, classification, semantic analysis, etc. is done from the aforementioned vectors on.

Here is a slide that explains this with a bit of algebra and some user friendly text.

Feel free to download and don’t forget to share.

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