NEURAL NETWORK (Artificial Neural Network : ANN)

NEURAL NETWORK :

• Neural Network (NN) are those information processing system which are constructed and implemented to model the human brain.
• The main objective of Neural Network is to develop a computational device for modeling the brain to perform various computational task at faster rate than the traditional system.

ARTIFICIAL NEURAL NETWORK :

• An Artificial Neural Network is a computational model based on the structure, concept, and functions of "Biological Neural Network" consists of number of neurons.

NEURAL NETWORK ARCHITECTURE :

• An Artificial Neural Network can be represented using directed graph which consists of highly interconnected processing elements known as "Artificial Neurons".
  
• There are 3 architecture of Artificial Neural Neetwork

1. Single Layered Feed Forward Network.
2. Multi Layered Feed Forward Network.
3. Recurrent Network 

Single Layered Feed Forward Network :

• The input layer neurons receive the input signals and the output layer neurons receive the output layers.
• The links carrying the weights connect every input neuron to the output neuron but not the process is vice-versa.So this is called as Feed Forward Network.
• Since the output layer  alone performs all the computations is called as Single Layered Feed Forward Network.

Multilayered Feed Forward Network :

• In this case Artificial Neural Network architecture consists of input and output layer with at least one intermediate layer known as hidden layer.
• Structure may be like I - H - O, I - H1 - H2 - O, I - H1 - H2 - H3 - O, etc.

Recurrent Network :

• In this network structure their exist a feedback link each of output neuron to the corresponding input neuron to give in the form of message for the completion of task.

• Artificial Intelligence is the backbone of  Machine Learning Techniques.