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- 1. Multiple Choice
1. What does a neuron compute?
A neuron computes an activation function followed by a linear function (z = Wx + b)
A neuron computes a linear function (z = Wx + b) followed by an activation function
A neuron computes a function g that scales the input x linearly (Wx + b)
A neuron computes the mean of all features before applying the output to an activation function
- 2. Multiple Choice
What activation function is it?
sigmoid
tanh
ReLU
ELU
- 3. Multiple Choice
What activation function is it?
sigmoid
tanh
ReLU
ELU
- 4. Multiple Choice
What activation function is it?
sigmoid
tanh
ReLU
ELU
- 5. Multiple Choice
How many hidden layers have the following Neural network
4
5
6
7
- 6. Multiple Choice
How many input layers have the following Neural network
1
2
3
4
- 7. Multiple Choice
What is a cost function?
function describes how computationally expensive is a neural network
an algorithm used to find the minimum of a function
different name for activation function
a way to determine how well the machine learning model has performed given the different values of each parameter
- 8. Multiple Choice
What is gradient descent?
a way to determine how well the machine learning model has performed given the different values of each parameter
method to increase the speed of Neural Network operation
an optimization algorithm used to find the values of parameters (coefficients) of a function (f) that minimizes a cost function (cost)
different name for activation function
- 9. Multiple Choice
How many output layers have the following Neural network?
1
2
3
4
- 10. Multiple Choice
What is activation function?
a way to determine how well the machine learning model has performed given the different values of each parameter
an optimization algorithm used to find the values of parameters (coefficients) of a function (f) that minimizes a cost function (cost)
function describes how computationally expensive is a neural network
function used to enable Neural Network to solve non-linear problems
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