Transformers are a type of neural network architecture that are used in natural language processing tasks like language translation, language modelling, and text classification. They are effective at converting words into numerical values, which is necessary for AI to understand language. There are three key concepts to consider when encoding words numerically: semantics (meaning), position (relative and absolute), and relationships and attention (grammar). Transformers excel at capturing relationships and attention, or the way words relate to and pay attention to each other in a sentence. They do this using an attention mechanism, which allows the model to selectively focus on certain parts of the input while processing it. In the next video, we will look at the attention mechanism in more detail and how it works.
We can encode word semantics using a neural network to predict a target word based on a series of surrounding words in a corpus of text. The network is trained using backpropagation, adjusti
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