Neural network

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[edit | edit source]

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[edit | edit source]

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[edit | edit source]

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[edit | edit source]

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

See Also[edit | edit source]

Neural network Resources
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