What Artificial Neural Network (ANN) Meaning, Applications & Example
A computational model inspired by biological neural networks.
What is an Artificial Neural Network?
An Artificial Neural Network (ANN) is a computing system inspired by the structure and function of the human brain. ANNs are composed of interconnected nodes (neurons) that process data and recognize patterns, enabling tasks like classification , prediction, and clustering .
Types of Artificial Neural Networks
- Feedforward Neural Network: Information moves in one direction, from input to output, commonly used in classification tasks.
- Convolutional Neural Network (CNN) : Specialized for image recognition and processing spatial data.
- Recurrent Neural Network (RNN) : Capable of processing sequential data, making it useful for language and time-series applications.
Applications of Artificial Neural Networks
- Image Recognition: ANNs can classify images, detect objects, and power facial recognition systems.
- Natural Language Processing (NLP) : Used for sentiment analysis , translation, and speech recognition.
- Financial Forecasting: ANNs help analyze trends, predict stock prices, and assess credit risks.
Example of an Artificial Neural Network
An example of an ANN is the Multilayer Perceptron (MLP), which has multiple layers of neurons and is commonly used for classification and regression tasks.