An artificial neural network (ANN) is a computational model inspired by the structure and functions of biological neural networks in the human brain. It consists of interconnected nodes, called neurons, which work together to process and analyze complex data.

Some commonly used artificial neural networks include:

1. Multi-layer Perceptron (MLP)

2. Convolutional Neural Network (CNN)

3. Recurrent Neural Network (RNN)

4. Long Short-Term Memory (LSTM)

5. Generative Adversarial Network (GAN)

6. Autoencoder

7. Radial Basis Function Network (RBFN)

These are just a few examples of the many types of artificial neural networks that are widely used in various applications such as image recognition, natural language processing, and predictive analytics.

LSTMs(Recurrent Neural Networks), Autoencoders, Transformers, and prompt engineering

An Artificial Neural Network (ANN) is a computational model inspired by how biological neural networks in the human brain process information.

Some commonly used ANNs are CNN, RNN, LSTM, and GAN.