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.
- Glossary > Letter: A
What does "Artificial Neural Network (ANN)" mean?

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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