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Quantitative Finance · Glossaire

Qu'est-ce que « Word embedding » ?

Definition 13.4 Machine Learning for Markets · Chapitre 13 — Text: From Bag of Words to Embeddings

A word embedding maps each word to a dense vector of a few dozen to a few thousand real numbers, learned so that words used in similar contexts get nearby vectors: by factorising a matrix of co-occurrence statistics, or by training a network to predict a word from its neighbours (Mikolov and co-authors, 2013).

Cosine similarities of word embeddings learned from the training headlines’ co-occurrences. Opposites that fill the same slot are as close as synonyms. Data: ml_text.pairs.
Figure 13.2. Cosine similarities of word embeddings learned from the training headlines’ co-occurrences. Opposites that fill the same slot are as close as synonyms. Data: ml_text.pairs.
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