Tag Archives | transformer

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The Transformer Model

We have already familiarized ourselves with the concept of self-attention as implemented by the Transformer attention mechanism for neural machine translation. We will now be shifting our focus on the details of the Transformer architecture itself, to discover how self-attention can be implemented without relying on the use of recurrence and convolutions. In this tutorial, […]

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The Transformer Attention Mechanism

Before the introduction of the Transformer model, the use of attention for neural machine translation was being implemented by RNN-based encoder-decoder architectures. The Transformer model revolutionized the implementation of attention by dispensing of recurrence and convolutions and, alternatively, relying solely on a self-attention mechanism.  We will first be focusing on the Transformer attention mechanism in […]

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A Tour of Attention-Based Architectures

As the popularity of attention in machine learning grows, so does the list of neural architectures that incorporate an attention mechanism. In this tutorial, you will discover the salient neural architectures that have been used in conjunction with attention. After completing this tutorial, you will gain a better understanding of how the attention mechanism is […]

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A Bird’s Eye View of Research on Attention

Attention is a concept that is scientifically studied across multiple disciplines, including psychology, neuroscience and, more recently, machine learning. While all disciplines may have produced their own definitions for attention, there is one core quality they can all agree on: attention is a mechanism for making both biological and artificial neural systems more flexible.  In […]

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