Neural Networks in TensorFlow QUIZ (MCQ QUESTIONS AND ANSWERS)

Total Correct: 0

Time:20:00

Question: 1

Which of the following is NOT a benefit of using batch normalization?

Reducing the impact of vanishing gradients

Improving model generalization

Reducing the need for regularization techniques like dropout

Increasing model interpretability

Question: 2

What is the primary purpose of using activation functions in neural networks?

Controlling model complexity

Introducing non-linearity

Preventing overfitting

Addressing the vanishing gradient problem

Question: 3

What is the primary purpose of using Leaky ReLU activation function?

Introducing non-linearity

Reducing overfitting

Addressing the vanishing gradient problem

Preventing dead neurons

Question: 4

Which of the following activation functions is NOT symmetric around the origin?

ReLU

Sigmoid

Tanh

Leaky ReLU

Question: 5

Which of the following initialization strategies involves sampling weights from a uniform distribution?

Zero initialization

Random initialization

He initialization

Glorot initialization

Question: 6

What is the primary purpose of using batch normalization along with dropout layers in a neural network?

Reducing overfitting

Increasing model interpretability

Controlling the learning rate

Accelerating convergence during training

Question: 7

Which of the following activation functions is prone to the "dying ReLU" problem?

Sigmoid

Tanh

Leaky ReLU

ReLU

Question: 8

Which initialization strategy involves setting all weights to zero?

Zero initialization

Uniform initialization

Random initialization

He initialization

Question: 9

What is the primary purpose of using dropout layers in neural networks?

Reducing overfitting

Accelerating convergence during training

Enhancing model interpretability

Controlling the learning rate

Question: 10

Which activation function is commonly used for multi-class classification tasks in the output layer of a neural network?

ReLU

Sigmoid

Tanh

Softmax

Question: 11

What is the primary purpose of using Xavier (Glorot) initialization?

Preventing overfitting

Speeding up convergence during training

Addressing the vanishing/exploding gradient problem

Regularizing the model

Question: 12

Which of the following is a technique used to prevent the saturation of neurons and speed up the training of deep neural networks?

L1 regularization

Gradient clipping

Xavier initialization

ReLU activation

Question: 13

What is the main drawback of using the sigmoid activation function?

Prone to vanishing gradients

Limited output range

Not differentiable at zero

None of the above

Question: 14

Which of the following initialization strategies is designed to address the vanishing/exploding gradient problem?

Zero initialization

Random initialization

He initialization

Glorot initialization

Question: 15

Which initialization strategy involves sampling weights from a Gaussian distribution with zero mean and a specified variance?

Zero initialization

Uniform initialization

Random initialization

He initialization

Question: 16

Which of the following is NOT a commonly used activation function in neural networks?

ReLU

Sigmoid

Tanh

MaxPooling

Question: 17

What does the dropout rate represent in a dropout layer?

The proportion of units to activate during training

The proportion of units to deactivate during training

The learning rate of the model

The regularization strength

Question: 18

Which of the following is a purpose of using an activation function in a neural network?

Controlling model complexity

Regularizing the model

Introducing non-linearity

Enhancing model interpretability

Question: 19

What does the 'ReLU' activation function stand for?

Rectified Linear Unit

Randomized Linear Enhancement

Restricted Linear Uptake

Regressive Linear Estimation

Question: 20

Which of the following is a drawback of using the ReLU activation function?

Prone to vanishing gradients

Only suitable for binary classification tasks

Not differentiable at zero

None of the above

Question: 21

Which activation function is preferred for the output layer of a binary classification neural network?

ReLU

Sigmoid

Tanh

Softmax

Question: 22

Which of the following initialization strategies is commonly used for neural network weights?

Uniform initialization

Zero initialization

Random initialization

All of the above

Question: 23

Which layer type is used to prevent overfitting by randomly dropping units during training?

Activation layer

Batch normalization layer

Dropout layer

Fully connected layer

Question: 24

What is the primary purpose of batch normalization in neural networks?

Reducing overfitting

Increasing model interpretability

Accelerating convergence during training

Controlling the learning rate

Question: 25

Which of the following activation functions is not continuous and differentiable?

ReLU

Sigmoid

Tanh

Leaky ReLU

Question: 26

Which of the following is a common strategy to determine the initial learning rate in training neural networks?

Grid search

Random search

Adaptive methods like Adam

Xavier initialization

Question: 27

What is the primary purpose of using weight initialization techniques in neural networks?

Accelerating convergence during training

Preventing overfitting

Addressing the vanishing gradient problem

Controlling the learning rate

Question: 28

Which of the following activation functions is NOT bounded?

Sigmoid

Tanh

ReLU

Leaky ReLU

Question: 29

What is the primary purpose of using L1 and L2 regularization techniques in neural networks?

Preventing overfitting

Accelerating convergence during training

Increasing model interpretability

Controlling the learning rate

Question: 30

Which of the following is a common technique used to address the vanishing gradient problem?

Gradient clipping

Xavier initialization

He initialization

Dropout layers

Neural Networks in TensorFlow QUIZ (MCQ QUESTIONS AND ANSWERS)

TIME:20:00

Time:20:00

Which of the following is NOT a benefit of using batch normalization?

What is the primary purpose of using activation functions in neural networks?

What is the primary purpose of using Leaky ReLU activation function?

Which of the following activation functions is NOT symmetric around the origin?

Which of the following initialization strategies involves sampling weights from a uniform distribution?

What is the primary purpose of using batch normalization along with dropout layers in a neural network?

Which of the following activation functions is prone to the "dying ReLU" problem?

Which initialization strategy involves setting all weights to zero?

What is the primary purpose of using dropout layers in neural networks?

Which activation function is commonly used for multi-class classification tasks in the output layer of a neural network?

What is the primary purpose of using Xavier (Glorot) initialization?

Which of the following is a technique used to prevent the saturation of neurons and speed up the training of deep neural networks?

What is the main drawback of using the sigmoid activation function?

Which of the following initialization strategies is designed to address the vanishing/exploding gradient problem?

Which initialization strategy involves sampling weights from a Gaussian distribution with zero mean and a specified variance?

Which of the following is NOT a commonly used activation function in neural networks?

What does the dropout rate represent in a dropout layer?

Which of the following is a purpose of using an activation function in a neural network?

What does the 'ReLU' activation function stand for?

Which of the following is a drawback of using the ReLU activation function?

Which activation function is preferred for the output layer of a binary classification neural network?

Which of the following initialization strategies is commonly used for neural network weights?

Which layer type is used to prevent overfitting by randomly dropping units during training?

What is the primary purpose of batch normalization in neural networks?

Which of the following activation functions is not continuous and differentiable?

Which of the following is a common strategy to determine the initial learning rate in training neural networks?

What is the primary purpose of using weight initialization techniques in neural networks?

Which of the following activation functions is NOT bounded?

What is the primary purpose of using L1 and L2 regularization techniques in neural networks?

Which of the following is a common technique used to address the vanishing gradient problem?