Neural Networks USE CASE

What Are Neural Networks?

A neural network is a network or circuit of neurons, or in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus a neural network is an artificial neural network, for solving artificial intelligence (AI) problems.

How Artificial Neural Networks Function

ANNs are statistical models designed to adapt and self-program by using learning algorithms in order to understand and sort out concepts, images, and photographs.. The input layer is analogous to the dendrites in the human brain’s neural network. The hidden layer is comparable to the cell body and sits between the input layer and output layer (which is akin to the synaptic outputs in the brain). The hidden layer is where artificial neurons take in a set of inputs based on synaptic weight, which is the amplitude or strength of a connection between nodes. These weighted inputs generate an output through a transfer function to the output layer.

Why Do We Use Neural Networks?

Neural networks’ human-like attributes and ability to complete tasks in infinite permutations and combinations make them uniquely suited to today’s big data-based applications. Because neural networks also have the unique capacity to make sense of ambiguous, contradictory, or incomplete data, they are able to use controlled processes when no exact models are available.

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Okra Technologies