2. Human and Machine Language

In Chapter 1, we introduced the high-level theory of deep learning via analogy to the biological visual system. All the while, we highlighted that one of the technique’s core strengths lies in its ability to learn features automatically from data. In this chapter, we build atop our deep learning foundations by examining how deep learning is incorporated into human language applications, with a particular emphasis on how it can automatically learn features that represent the meaning of words.

The Austro-British philosopher Ludwig Wittgenstein famously argued, in his posthumous and seminal work Philosophical Investigations, “The meaning of a word is its use in the language.”1 He further wrote, “One cannot guess how ...

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