Deep Learning - Deep Neural Network for Beginners Using Python - Basics of Backpropagation

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Information Technology (IT), Architecture, Physics, Science
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7 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does a thicker line represent in the context of weights associated with inputs?
An inactive weight
A lighter weight
A heavier weight
A neutral weight
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary goal of backpropagation in a neural network?
To decrease the number of inputs
To add more layers to the network
To minimize the error by adjusting weights
To increase the number of neurons
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In the context of backpropagation, what happens to the weights of a model that is performing well?
The weights are reset to zero
The weights are decreased
The weights are increased
The weights remain unchanged
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does gradient descent help in reducing error in a neural network?
By increasing the learning rate
By adjusting weights in the direction of the steepest ascent
By adjusting weights in the direction of the steepest descent
By adding more neurons to the network
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the role of partial derivatives in updating weights during backpropagation?
They determine the learning rate
They help in calculating the error
They increase the number of layers
They are used to calculate the gradient for weight updates
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the prediction formula used in the context of logistic regression?
Y = W * X * B
Y = W + X + B
Y = sigmoid(WX + B)
Y = WX + B
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the significance of the bias term 'B' in the prediction formula?
It is used to decrease the error
It is used to scale the inputs
It is not used in the prediction formula
It acts as a threshold for activation
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