Consider the neural network shown below. The network consists of 2 input values (x1, x2) with their associated weights (0.3, 0.4, 0.3) and (0.2, 0.7, 0.1), 3 nodes in the hidden layer (h1, h2, h3) with associated weights (0.3, 0.5, 0.2) for target output. Assume all neurons have the same bias b = 0.2, and the same sigmoid activation function. If we input (x1, x2) = [1, 2], what will be the network’s output?
Consider the neural network shown below. The network consists of 2 input values (x1, x2) with their associated weights (0.3, 0.4, 0.3) and (0.2, 0.7, 0.1), 3 nodes in the hidden layer (h1, h2, h3) with associated weights (0.3, 0.5, 0.2) for target output. Assume all neurons have the same bias b = 0.2, and the same sigmoid activation function. If we input (x1, x2) = [1, 2], what will be the network’s output?
Principles of Information Systems (MindTap Course List)
12th Edition
ISBN:9781285867168
Author:Ralph Stair, George Reynolds
Publisher:Ralph Stair, George Reynolds
Chapter7: The Internet, Web, Intranets, And Extranets
Section7.6: Information Systems @ Work: Improved Insight Via Clickstream Analysis
Problem 1CTQ
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Consider the neural network shown below. The network consists of 2 input values (x1, x2) with their associated weights (0.3, 0.4, 0.3) and (0.2, 0.7, 0.1), 3 nodes in the hidden layer (h1, h2, h3) with associated weights (0.3, 0.5, 0.2) for target output. Assume all neurons have the same bias b = 0.2, and the same sigmoid activation function.
If we input (x1, x2) = [1, 2], what will be the network’s output?
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