Everything is just numbers… even letters!

Yes, for a machine, everything boils down to numbers. But then, how does it manage to understand what I’m asking?

Today, let’s dive a little deeper into the world of NLP (Natural Language Processing).

In reality, the goal of NLP is to uncover the hidden mathematical relationships behind the arrangement of letters and words.

Let me give you a concrete example:

If I ask you to complete this sentence: “I eat …”, you could naturally complete it with “rice,” “corn,” or another food.

Why? Because the verb “eat” pushes you to choose a word related to food.

However, you would make a mistake if you completed it with “stick” or “notebook.”

This shows that the presence of a word in a sentence is influenced by other words around it, and even by the context of previous sentences.

Our goal, then, will be to understand all these hidden relationships between words and sentences. These relationships are what we call models.

And for a machine to uncover these relationships, it needs to read a large number of texts, analyze millions of words, and understand the connections between them. This collection of texts is called a dataset.

In summary: NLP allows machines to understand human language by discovering the patterns and hidden relationships behind our words.

See you tomorrow for the next part ⭐