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# Artificial Neural Networks

## What is an Artificial Neural Network?
An artificial neural network (ANN) is a type of machine learning algorithm that is based on the structure of biological neural networks. ANNs are composed of interconnected nodes, which represent neurons in the brain, and can be used to model complex relationships between inputs and outputs. ANNs are used for a variety of tasks such as classification, regression, and clustering.

## How do Artificial Neural Networks Work?
ANNs are composed of layers of interconnected nodes (neurons) that communicate with each other. Each neuron has an associated weight, which determines how much influence it has on the output of the network. The weights are adjusted based on the input data and the desired output. This process is known as training or learning. Once trained, the ANN can be used to make predictions or classifications based on new input data.

## What are some Applications of Artificial Neural Networks?
ANNs have been used for a variety of tasks such as image recognition, natural language processing, and robotics control. They have also been used in medical applications such as diagnosing diseases and predicting patient outcomes. Additionally, ANNs have been used in finance to predict stock prices and credit scores.