Deep Learning

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

What activation function is it?

• sigmoid

• tanh

• ReLU

• ELU

What activation function is it?

• sigmoid

• tanh

• ReLU

• ELU

What activation function is it?

• sigmoid

• tanh

• ReLU

• ELU

How many hidden layers have the following Neural network

• 4

• 5

• 6

• 7

How many input layers have the following Neural network

• 1

• 2

• 3

• 4

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

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

How many output layers have the following Neural network?

• 1

• 2

• 3

• 4

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