What is deep learning?

What is a transformer neural net?

A type of neural network architecture known as transformers is gaining popularity. Transformers were created to solve the problem sequence transduction or neural translation. This refers to any task that converts an input sequence into an output sequence.

What is an attention mechanism in deep-learning? If we look at the English word Attentiona we can see that it refers to directing our attention towards something and paying more attention. This concept of directing your attention is the basis for Deep Learning's Attention mechanism. It pays more attention to certain factors while processing data.

What is transformer attention in this context?

According to the Transformer Paper, Attention is defined as: The Transformer Paper explains the definition of attention. A attention function is a mapping of a query (Q), a set key-value pairs(K, V), to an output. The query, keys, values and output are all vectors.

What are encoder and decoders in deep learning?

A deep learning encoder/decoder is a technique that is used mostly in text generation. These are used mainly in text translation models. Generally speaking, the encoder converts the input sequence into an internal representation called the 'context vector'. This is then used by decoders to generate the output sequence.