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'''Neural Network'''

A '''[[Neural Network]]''' is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. In essence, neural networks are used to approximate functions that can depend on a large number of inputs and are generally unknown.

== Overview ==

Neural networks, in the world of [[Artificial Intelligence]], are a means of doing [[machine learning]], in which a computer learns to perform some task by analyzing training examples. Usually, the task involves making predictions or decisions, such as: Is this an image of a cat? Which of these people are likely to be friends? What is the optimal path for a delivery drone?

== Structure ==

A neural network takes in inputs, which are then processed in hidden layers using weights that are adjusted during training. Then the model spits out a prediction. The weights are adjusted to find patterns in order to make better predictions.

== Types of Neural Networks ==

There are several types of neural networks in use today. These include:

* '''[[Feedforward Neural Network]]''' - Artificial Neuron
* '''[[Radial basis function Neural Network]]'''
* '''[[Multilayer Perceptron]]'''
* '''[[Convolutional Neural Network]]'''
* '''[[Recurrent Neural Network(RNN)]]''' - Long Short Term Memory
* '''[[Modular Neural Network]]'''

== Applications ==

Neural networks have wide applications in the fields of [[biometrics]], [[finance]], [[healthcare]], and [[telecommunications]], among others.

== See Also ==

* [[Artificial Intelligence]]
* [[Machine Learning]]
* [[Deep Learning]]
* [[Artificial Neural Network]]

[[Category:Artificial Intelligence]]
[[Category:Machine Learning]]
[[Category:Neural Networks]]

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Neural network - Revision history

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