Consider a two-layer neural network with two inputs a and b, one hidden unit c, and one output unit d. This network has five weights (wac» Wbc+ Woc• Wcd» Woa), where woc and wod represent the weights associated with bias inputs. Assume that: (1) all the weights are initialized to 0.1; (2) the learning rate is 0.3; (3) the input for the two biases is -1; and (4) c and d are sigmoid units. Use the following approximate values for o where necessary below: o(x) -0.5 < x < - 2.5 -2.5 < x < - 0.05 -0. 05 < x < 0 0.001 0.20 0.49 0.5 0 < x < 0. 05 0. 05 < x < 2.5 2.5 < x < 5.0 0.51 0.80 0.999 Consider the following training example for the network described above: a = 1, b = 0, d = 1

Add formulas to complete the table of hours used. In cell B17, create a nested formula with the IF and SUM functions that check if the total number of hours worked in week 1 (cells B9:F9) is equal to 0. If it is, the cell should display nothing (indicated with two quote marks: ""). Otherwise, the cell should display the total number of hours worked in week 1. Copy the formula from cell B17 to fill the range B18:B20

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BoxPlots are centric to : (Select one) a) mean  b) median  c) mode d) Q1