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61. Which of the following gives non-linearity to a neural network.
Convolution operator
Stochastic gradient descent
Sigmoid activation
Non-zero bias
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62. Consider a two input neuron with logistic activation function with slope parameter a = 2. Let the inputs be [-1, 1] and the weights are [0.1, 0.5] respectively. The output of the neuron is 0.73. The value of the bias b1 is (Round bias value till 1 decimal point)?
(type: Range) 0.09,0.11
(type: Range) 0.08,0.10
(type: Range) 0.08,0.11
(type: Range) 0.09,0.10
63. Consider a fully connected feedforward network (with a single hidden layer) with no self loops. The network takes inputs of dimension 100 and consists of 5000 hidden neurons. What are the total number of connections between the input and the hidden layer?
5 x 103
1 x 105
5 x 105
1005000
64. Consider the neural network below. Find the appropriate weights for w0, w1 and w2 to represent the AND function. Threshold function = {1, if output >0; 0 otherwise}. x0 and x1 are the inputs and b1 = 1 is the bias.
W0-1, w1-1, w2-1
W0 = 1, w1 = 1, w2 = -1
W0 = -1, w1 = -1, w2 = -1
W0 = 2, w1 = -2, w2 = -1
65. Which of the combination of weights make the network represent OR function:
w0 = 1, w1 = 1, w2 = 0
w0 = 1, w1 = 1, w2 = -1
w0 = -1, w1 = -1, w2 = -1
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