Understanding Tokenization and Embedding in Natural Language Processing
By
zdw
Lightly toasted, lightly seasoned, mostly correct.
Summary
The article discusses the tokenization and embedding process in natural language processing, likening it to a path through a vector space. It explores the concept of mapping words to vectors and visualizes text as a journey through this space.
Key quotes
· 2 pulledThe tokenization and embedding step maps individual words (or tokens) to some \(\mathbb{R}^n\) vectors.
A piece of text is then a path through this space - going from word to word to word, tracing a (possibly convoluted) line.
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