NLP Illustrated, Part 1: Text Encoding | by Shreya Rao | Nov, 2024


An illustrated guide to text-to-number translation, with code

Shreya Rao

Towards Data Science

Welcome back to the corner of the internet where we take complex-sounding machine learning concepts and illustrate our way through them — only to discover they’re not that complicated after all!

Today, we’re kicking off a new series on Natural Language Processing (NLP). This is exciting because NLP is the backbone of all the fancy Large Language Models (LLMs) we see everywhere — think Claude, GPT, and Llama.

In simple terms, NLP helps machines make sense of human language — whether that means understanding it, analyzing it, or even generating it.

If you’ve been following along our Deep Learning journey, we’ve learned that at their heart, neural networks operate on a simple principle: they take an input, work their mathematical magic, and spit out an output.

For neural networks to do this though both the input and the output must be in a format they understand: numbers.

This rule applies whether we’re working with a straightforward model…



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