GATE DA 2026 Set 1 — Question 56
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Machine Learning → Neural Networks → Feed-Forward Networks
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Question
Consider a fully-connected feed-forward multi-layer perceptron. It has 30 neurons in the input layer, followed by two hidden layers and an output layer. The first hidden layer has 4 neurons and the second hidden layer has 3 neurons. The output layer has only one neuron. Assume that no bias parameters are used. The number of learnable parameters in the multi-layer perceptron is __________ . (Answer in integer)
Correct answer
135 to 135
Solution
In a fully-connected feed-forward neural network without bias parameters, the number of learnable parameters (weights) between two adjacent layers with and neurons is .Given architecture:
- Input layer (): 30 neurons
- Hidden layer 1 (): 4 neurons
- Hidden layer 2 (): 3 neurons
- Output layer (): 1 neuron
1.Between Input layer and Hidden layer 1:
2.Between Hidden layer 1 and Hidden layer 2:
3.Between Hidden layer 2 and Output layer:
Total learnable parameters = .Continue learning with Success Tracker
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