Core techniques for teaching computers to understand text.
The first step: cleaning text and breaking it into tokens.
Representing words as dense vectors that capture semantic meaning.
The encoder-decoder architecture for tasks like machine translation.
Allowing models to focus on relevant parts of the input sequence.