Consider the following training set input values х'%3D (1, x? = (0, x'= (- 1, No. desired output value 1. 0, - 1, - 0.5, - 1)" 1)" -1 2. - 1)" 1 3. 1 Assume the learning rate is 0.1 and the initial weight vector is w, = (1, -1, 0)". After training draw the neural network.

Q: Suppose that we use sigmod activation function and square loss function: (t- o)2. The learning rate…

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A: The correct statement is: Neurons compute a linear function (z = Wx + b) and an activation function.…

Q: q(the/",") = 1 q(dog/",the) = 0.5 q(STOPI", the) = 0.5 q(runs/the, dog) = 0.5 q(STOP/the, dog) 0.5…

A: we would have V = {the, dog, runs},p(the dog barks STOP) = q(the|*, *) = 1 q(dog|*, the)  = 0.5…

Q: Design a one-layered Neural Network for these

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Q: Assume that you are using YOLO on a 15x15 grid, for a detection problem with 5 different classes…

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A: ANSWER:-

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Q: Apply the backpropagation algorithm to the neural network given below. Find the weights after the…

A:

Q: The weights, activation function, and set of input values for a Neural Network are given below:…

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Q: For a fixed integer C > 0, given a sequence of {r;}{1, and {y:}E=1 with y: = (E=max{t-C,1} T3)°,…

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Q: Suppose we have a neural net, which we denote as a function F(x; 0), that performs binary logistic…

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Q: Consider the following neural network. In order to have some numbers to work with, here are the…

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Q: The learning problem is to find the unknown (functional) relationship hy between objects x X and…

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Q: ider the following neural network. Assume that outputs O1, are outputs of sigmoid activation…

A:

Q: We are given the following training examples in 2D ((-3,5), +), ((-4, –2), +), ((2,1), -), ((4,3),–)…

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Q: Error versus Weight Updates (Example 1) 0.01 Training set error Validation set error 0.009 0.008…

A: Q.