Before the state of the art transformer was developed, early models were used to solve Natural Language Processing problems. These models were the Naive bayes classifier, the recurrent neural network, ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI.

The basic idea, as I understand it, is to achieve cross-domain generality by recreating the MLP with transformers, where "neurons" and activations are vectors not scalars, and interlayer weights ...

This project is an attempt of implementing transformers deep neural architecture where the neural network is learning a language model based on a corpus of text. Once trained, the network is able to ...