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Artificial Neural Network (ANN)

An artificial neural network (ANN) is a computing system inspired by the biological neural networks in animal brains. It consists of layers of interconnected nodes (neurons) where each connection represents a weight-adjusted during learning. ANNs are used to recognize patterns, classify data, and make predictions.

Use Cases

Image Recognition

Identifying objects, people, and scenes in images.

Speech Recognition

Converting spoken language into text.

Financial Services

Predicting stock prices and detecting fraudulent activities

Importance

Pattern Recognition

Excels at identifying patterns in large and complex datasets. Versatility: Can be applied to various fields such as healthcare, finance, and entertainment.

Learning Ability

Improves performance over time as it learns from more data, crucial for dynamic industries like news & media.

Scalability

Capable of handling large datasets and complex computations, making it suitable for enterprise-grade applications.

Analogies

An ANN is like a group of people working together to solve a problem. Each person (neuron) has a piece of information (weight) and they collectively work through layers of communication to reach a solution.

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