Artificial Neural networks, simply called Neural networks, are computer systems based on units called nodes or artificial neurons, which resemble the neurons in human brains. Each node can transmit a signal from one node to another. 

An Artificial Neural Network

A neural network includes SEVERAL layers, each of which performs a specialized job. As the model's complexity grows, the NUMBER of layers grows as well, which is why it's called a multi-layer perceptron.

A neural network in its purest form includes three layers: an INPUT layer, a hidden layer, and an output layer. The input layer receives the input SIGNALS and passes them on to the next layer, with the output layer delivering the final prediction. These neural networks, like machine learning methods, must be taught with some training data before being used to solve a specific problem. Let's learn more about the perceptron now.

An ANN CONSISTS of multiple layers including an input layer, an output layer, and hidden layers. Some commonly used ANN are:

• Feed Forward Neural Network
• Convolution Neural Network
• Recurrent Neural Networks
• Auto-encoders.