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Engineering AI and Machine Learning

Figure Q4 shows a fully connected feed-forward neural network, being fed with a single input instance of [1.0, 0.4, 0.7]. Initial weight values for the network are given in Table Q4. Calculate the output value for the given input. In your answer, use the Rectified Linear Unit (ReLU) as the activation function.

Figure Q4 shows a fully connected feed-forward neural network, being fed with a single input instance of [1.0, 0.4, 0.7]. Initial weight values for the network are given in Table Q4. Calculate the output value for the given input. In your answer, use the Rectified Linear Unit (ReLU) as the activation function.

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Figure Q4 shows a fully connected feed-forward neural network, being fed with a single input instance of [1.0, 0.4, 0.7]. Initial weight values for the network are given in Table Q4. Calculate the output value for the given input. In your answer, use the Rectified Linear Unit (ReLU) as the activation function. (20MARKS)

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Transcribed Image Text:1.0 0.4 0.7 W11 0.20 Node 1 Node 2 Node 3 W1 li Wij W2j W 3i Node j Node i Wijk ik Node k Figure Q4 Table Q4: Initial weight values or the neural network W31 W31 Wik W1i W21 Wzi Wik 0.10 0.30 -0.10 -0.10 0.20 0.10 0.50

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Step 1: To calculate the output value for the given input, we need to follow these steps:

Step 2: Finally, we substitute the given values for the weights and inputs into the equations and simplify:

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