Notes for B.4.2 Structure of Neural Networks - IB | RevisionDojo
B.4.2 Structure of Neural Networks Notes
Definition
Neural Network
A computational model inspired by the human brain, consisting of interconnected nodes (neurons) that process data in layers to recognize patterns and solve complex problems.
Neural networks are a fundamental component of artificial intelligence (AI), designed to mimic the way the human brain processes information.
They are particularly powerful for tasks such as image recognition , natural language processing , and predictive analytics.
Structure of Neural Networks
The basic structure of a neural network consists of three types of layers:
Input Layer
Hidden Layers
Output Layer
Input Layer
The input layer is where the neural network receives data.
Each node (or neuron) in this layer represents a feature of the input data.
Example
In an image recognition task, each node might represent the pixel value of an image.
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Note
Introduction to Neural Network
A neural network is a computational model inspired by the human brain, consisting of interconnected nodes (neurons) that process data in layers to recognize patterns and solve complex problems.
Neural networks are a fundamental component of artificial intelligence (AI), designed to mimic the way the human brain processes information.
They are particularly powerful for tasks such as image recognition, natural language processing, and predictive analytics.
DefinitionNeural NetworkA computational model inspired by the human brain, consisting of interconnected nodes (neurons) that process data in layers to recognize patterns and solve complex problems.
AnalogyThink of a neural network like a complex web of interconnected roads, where each intersection (neuron) processes information and passes it along to the next intersection.
