Choosing the Right Model Architecture

Considering the available architecture possibilities, there are two popular architectures that are often used as starting points for several applications: Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). These are foundational networks and should be considered starting points for most projects.

We also include descriptions of another three networks, due to their relevance in the field: Long Short-Term Memory (LSTM) networks (an RNN variant); Generative Adversarial Networks (GANs); and Deep Reinforcement Learning (DRL). These latter architectures have shown great success in solving contemporary problems, however, they are slightly difficult to use. The next section will cover the use of different types of architecture in different problems.

Convolutional Neural Networks (CNNs)

CNNs have gained notoriety for working with problems that have a grid-like structure. They were originally created to classify images,...