Neural Networks Quiz

What is the main difference between linear regression and logistic regression?

• Linear regression predicts probabilities, logistic regression predicts values

• Linear regression is for classification, logistic regression is for regression

• Linear regression outputs continuous values, logistic regression outputs probabilities

• Both are the same except for the optimizer used

What is an activation function used for in a neural network?

• To normalize input data

• To add bias to a neuron

• To introduce non-linearity to the network

• To adjust the weights

What is the role of bias in a neural network?

• Prevents overfitting

• Adds flexibility by shifting the activation function

• Improves gradient descent

• Reduces training time

What do hidden layers in a neural network do?

• Store the final predictions

• Normalize the data

• Process input data through weighted sums and activation functions

• Store training labels

Is CAPTCHA an example of a neural network?

• Yes, it is a neural network model

• No, it’s a training dataset

• CAPTCHA uses neural networks to recognize inputs

• It is a programming language

Which of the following is NOT an example of a neural network?

• Convolutional Neural Network

• Recurrent Neural Network

• Decision Tree

• Feedforward Neural Network

What does ReLU stand for?

• Rectified Linear Unit

• Random Line Update

• Recurrent Learning Unit

• Rectangular Logic Unit

How does ReLU reduce the vanishing gradient problem?

• It forces gradients to 0

• It squares the gradients

• It has a constant gradient of 1 for positive inputs

• It uses a tanh curve

What is the job of an optimizer?

• To test data

• To increase model complexity

• To adjust weights and minimize loss

• To create activation functions

What’s the difference between "loss" and "loss function"?

• Loss is a function, loss function is a result

• Loss is calculated using a loss function

• Loss is fixed, loss function changes

• There is no difference