Artificial Neural Network (ANN)

1. Artificial Neural Network is a computational model based on the structure and function of biological neural network.
2. ANN is like an artificial human nervous system for receiving, processing and transmitting information in terms of computer science.
3. ANN is the imitation of Human nervous system.
4. ANN has incredible ability to learn from data and from environment.
5. ANN is the heart of the products such as Self driving cars, image recognition, etc.

Components of Human Neuron

1. Dendrite: It takes input from the other neuron in the form of electrical impulse.
2. Cell body: It generates inferences received from those inputs and decides what action to take.
3. Axon terminal: It transmits the output in the form of electrical impulse.

Components of Artificial Neural Network

1. Input Layer: It communicates with the external environment that presents a pattern to the neural network. Its job is to deal with all the inputs only. This input gets transferred to the hidden layers. Every input neuron should represent some variable that has an influence over the output of the neural network. The training observations are feed through these neurons.
2. Hidden Layer: These are the intermediate layers between input and output layers which helps the neural network learn the complicated relationships involved in the data. Its job is to process the inputs obtained by its previous layer. So it is the layer which is responsible for extracting the required feature from the input data.
3. Output Layer: It collects & transmits the information accordingly in way it has been designed to give. The pattern presented by the output layer can be directly traced back to the input layer. The final output is extracted from previous hidden layers.