Consider a neural network with two input nodes ¤1 and x2, two hidden nodes h1 and h2 and one output node o. All nodes have sigmoid activation functions. The weights for the connections are as follows:

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Neural Networks and Gradient Descent
17. Consider a neural network with two input nodes x1 and x2, two hidden nodes h1 and h2
and one output node o. All nodes have sigmoid activation functions. The weights for the
connections are as follows:
Connection Weight
xi → hi
0.5
X1 → h2
X2 → hj
X2 → h2
hi → o
-0.9
0.1
-0.7
0.8
h2 → o
0.1
Table 3: Neural Network Weights
Transcribed Image Text:Neural Networks and Gradient Descent 17. Consider a neural network with two input nodes x1 and x2, two hidden nodes h1 and h2 and one output node o. All nodes have sigmoid activation functions. The weights for the connections are as follows: Connection Weight xi → hi 0.5 X1 → h2 X2 → hj X2 → h2 hi → o -0.9 0.1 -0.7 0.8 h2 → o 0.1 Table 3: Neural Network Weights
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