Machine Learning week 4 quiz: Neural Networks: Representation
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Neural Networks: Representation
5 试题
Which of the following statements are true? Check all that apply.
A two layer (one input layer, one output layer; no hidden layer) neural network can represent the XOR function.
The activation values of the hidden units in a neural network, with the sigmoid activation function applied at every layer, are always in the range (0, 1).
Suppose you have a multi-class classification problem with three classes, trained with a 3 layer network. Let
Any logical function over binary-valued (0 or 1) inputs
Consider the following neural network which takes two binary-valued inputs
OR
AND
NAND (meaning "NOT AND")
XOR (exclusive OR)
Consider the neural network given below. Which of the following equations correctly computes the activation
You have the following neural network:
You'd like to compute the activations of the hidden layer
You want to have a vectorized implementation of this (i.e., one that does not use for loops). Which of the following implementations correctly compute
z = Theta1 * x; a2 = sigmoid (z);
a2 = sigmoid (x * Theta1);
a2 = sigmoid (Theta2 * x);
z = sigmoid(x); a2 = sigmoid (Theta1 * z);
You are using the neural network pictured below and have learned the parameters
It will stay the same.
It will increase.
It will decrease
Insufficient information to tell: it may increase or decrease.
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