What is skip-gram?
A type of neural network architecture used for word embedding
skip-gram explained in plain English
Analogy
Imagine you're trying to learn the meaning of a word by looking at the words that are often used around it in a sentence. The skip-gram model is like a computer program that does this for all the words in a language, creating a map of word meanings.
Example
Google's Word2Vec algorithm uses the skip-gram model to create vector representations of words, which can be used to improve search results and language translation.
How is skip-gram used?
The skip-gram model is used in natural language processing tasks such as language modeling, text classification, and machine translation.
Common misconceptions about skip-gram
Some people think that the skip-gram model is only used for language modeling, but it can be used for a wide range of NLP tasks.
History
The skip-gram model was introduced in 2013 by Mikolov et al. as a way to improve the efficiency of word embedding algorithms.
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