Neural Networks are artificial systems that have a lot of resemblance to the biological neural networks in the human body. A neural network is a set of algorithms that attempts to recognize underlying relationships in a batch of data using a method that mimics how the human brain works. Without any task-specific rules, these systems learn to do tasks by being exposed to a variety of datasets and examples. The notion is that instead of being programmed with a pre-coded understanding of these datasets, the system derives identifying traits from the data it is fed to. Neural networks are built on threshold logic computational models. Because neural networks can adapt to changing input, they can produce the best possible outcome without requiring the output criteria to be redesigned.
