Artificial Intelligence — CBSE Class 10 board question

Neural Networks:
Neural networks are loosely modelled after how neurons in the human brain behave. They can extract data features automatically without needing input from the programmer. A neural network is a system of organising machine learning algorithms to perform certain tasks. It is fast and efficient for solving problems with very large datasets, such as images.

Layers of a Neural Network:

1. Input Layer: The first layer. It acquires data and feeds it to the network. No processing occurs here.

1. Hidden Layer(s): These layers perform all the processing using weights and biases on each node. Each node runs its own machine learning algorithm on the received data. There can be multiple hidden layers depending on the complexity of the task.

1. Output Layer: The last layer. It receives the final processed data from the hidden layers and presents it to the user. Like the input layer, no processing occurs here.

Source: Chapter 2, Section 2.3 – Artificial Neural Networks

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• The question is worth 4 marks, so examiners expect: a brief definition (1 mark) + explanation of all three layers with their roles (3 marks — 1 each).
• Key phrase to remember: "no processing at input/output layer" — this is a commonly tested point.
• Mention weights and biases for the hidden layer to show accurate understanding.
• Do not confuse "multiple hidden layers" with separate marks — mention it as a feature of the hidden layer briefly.