What Is Neural Network Classifier

A neural network consists of units (neurons), arranged in layers, which convert an input vector into some output. Each unit takes an input, applies a (often nonlinear) function to it and then passes the output on to the next layer.

Why do we use neural networks for classification?

Neural networks help us cluster and classify. You can think of them as a clustering and classification layer on top of the data you store and manage. They help to group unlabeled data according to similarities among the example inputs, and they classify data when they have a labeled dataset to train on.

Is neural network classification or prediction?

Get in touch. As we said in our earlier post, an artificial neural network (ANN) is a predictive model designed to work the way a human brain does. In fact, ANNs are at the very heart of deep learning.