Types of RNN Architectures
Explore various Recurrent Neural Network architectures and their applications in NLP. Learn how one-to-one, one-to-many, many-to-one, many-to-many, and encoder-decoder RNN types function and apply to tasks such as sentiment analysis, image captioning, POS tagging, speech recognition, and machine translation.
We'll cover the following...
We'll cover the following...
In this lesson, we are going to discuss different variations of Recurrent Neural Networks and their applications. So let’s get started.
Types of RNN architectures
There are five types of RNN architectures:
One to one (non-sequential)
This is the most simple one. It basically represents a Multi-Layer Perceptron because it takes a single input and generates a single output. The architecture is depicted below.
It generally isn’t used for image classification tasks as we have CNN to do this ...