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What is the main role of hidden layers in a neural network?

Answer and explanation

Correct answer: To learn complex patterns and useful features from the input

Hidden layers are positioned between the input and output layers. Their neurons combine inputs through weights, apply activation functions, and transform representations step by step. With training, these layers learn useful features and increasingly complex patterns. Hence A is correct. The input layer receives raw data, the output layer generally gives the final prediction, and weights are not a permanent data store.

Related tags

Artificial IntelligenceNeural NetworksHidden LayersFeature LearningUnit 6: Understanding Neural NetworksUnit 6 Understanding Neural NetworksPart B: Subject Specific SkillsPart B Subject Specific Skills

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