Adding a Custom Attention Layer to a Recurrent Neural Network in Keras
Deep learning networks have gained immense popularity in the past few years. The “attention mechanism” is integrated with deep learning networks to improve their performance. Adding an attention component to the network has shown significant improvement in tasks such as machine translation, image recognition, text summarization, and similar applications.
This tutorial shows how to add a custom attention layer to a network built using a recurrent neural network. We’ll illustrate an end-to-end application of time series forecasting using a very simple dataset. The tutorial is designed for anyone looking for a basic understanding of how to add user-defined layers to a deep learning network and use this simple example to build more complex applications.
After completing this tutorial, you