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Neural Network

A process of quantifying text information from focus groups by coding appropriately into a computer and then analyzing results. When using a computer, results can identify patterns, draw abstractions, and find relationships within the input data.

What is a neural network concept?

Modeled in accordance with the human brain, a Neural Network was built to mimic the functionality of a human brain. The human brain is a neural network made up of multiple neurons, similarly, an Artificial Neural Network (ANN) is made up of multiple perceptrons (explained later). See the full article for more details.

Why do we need neural networks?

Neural networks are a computing system with interconnected nodes that work more like the neurons in a human brain. Neural networks are used to solve complex problems people face in real-world situations. These networks can learn and model the relationships between inputs and outputs that are complex and nonlinear.

What are the advantages of neural networks?

Neural networks offer a number of advantages, including requiring less formal statistical training, ability to implicitly detect complex nonlinear relationships between dependent and independent variables, ability to detect all possible interactions between predictor variables, and the availability of multiple training.

Which neural network is the simplest network?

The perceptron is the oldest neural network, created all the way back in 1958. It is also the simplest neural network. Developed by Frank Rosenblatt, the perceptron set the groundwork for the fundamentals of neural networks. This neural network has only one neuron, making it extremely simple.

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