How does Word2Vec work?
An example of an AI chatbot conversation about Word2Vec and its functionality.
Can you explain how Word2Vec works?
Sure! Word2Vec is a technique used to convert words into numerical vectors, capturing their meanings.
How does it capture the meaning of words?
It uses neural networks to analyze the context of words in large text corpora, learning word associations.
What are the two main models used in Word2Vec?
The two main models are Continuous Bag of Words (CBOW) and Skip-Gram, each processing context differently.
Can you give an example of how it works?
Certainly! In the Skip-Gram model, if 'cat' is the target word, it predicts surrounding words like 'the', 'is', 'on'.
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