Word Application - CAIQ

Increase your daily file routines with Word Application - CAIQ

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Get a free DocHub user profile to start working on your files.
Register your account with your email address, Google account, or SSO.
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Save changes and come back to your file anytime, or create a Template for the most frequently used documents.
Save, download, or share your finished file with your teammates or customers to gather signatures.

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How to Word Application - CAIQ

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hey everyone welcome to the semicolon in this video well be learning about a very popular method for representing text called word Word2vec so machine learning and deep learning algorithms cannot accept text directly we need some sort of numerical representation so that the algorithms can process the data and in simple machine learning applications we use count vectorizer or tf-idf both of which do not preserve any relationship between the words this is where word embeddings come in they map all the words in a language into a vector space of a given dimension so word2vec is a popular method to generate word embeddings this converts words into vectors and with vectors we have multiple operations like add subtract calculate distance and that is how the relationship among the words are preserved so one example of this relationship is a very famous result of word2vec which says the vector of the king - man + woman gives you the word vector of the word Queen

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