Introduction of Word2vec: Learning Word Embeddings

Overview

In this chapter, we’ll discuss a topic of paramount importance in NLP—Word2vec, a data-driven technique for learning powerful numerical representations (that is, vectors) of words or tokens in a language. Languages are complex. This warrants sound language understanding capabilities in the models we build to solve NLP problems. When transforming words to a numerical representation, a lot of methods aren’t able to sufficiently capture the semantics and contextual information that a word carries. For example, the feature representation of the word “forest” should be very different from ...