Artificial Neural Networks, as the name suggests, are brain-inspired systems that are intended to replicate the way humans learn. Neural networks consist of input and output layers, as well as a hidden layer consisting of units that transform the inputs into optimal outputs. They are excellent tools to find patterns that are far too complex or numerous for a human programmer to extract and teach the machine to recognize.
Some of the commonly used ones include:
- Feed Forward Neural Nets
- Multiple Layered Perceptron Neural Nets
- Convolution Neural Nets
- Recurrent Neural Nets
- Modular Neural Network