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Introduction to Artificial Neural Networks
Artificial Neural Networks (ANNs) are computational models inspired by the structure and functioning of the human brain. They are designed to recognize patterns, learn from data, and make decisions with minimal human intervention. ANNs are a core component of modern artificial intelligence systems, enabling machines to perform tasks such as image recognition, language translation, and predictive analysis. By simulating networks of interconnected neurons, these systems can process complex information and improve their performance over time through learning.
Basic Structure and Components of ANN
An artificial neural network consists of layers of interconnected nodes, commonly referred to as neurons. These layers typically include an input layer, one or more hidden layers, and an output layer. Each neuron receives input signals, processes them using weights and biases, and produces an output through an activation function. The weights determine the importance of each input, while biases help shift…