Neural Networks MCQs With Answers

Computer MCQs 360April 10, 2024

0 12 1 minute read

Welcome to the Neural Networks MCQs with Answers. In this post, we have shared Neural Networks Online Test for different competitive exams. Find practice Neural Networks Practice Questions with answers in Computer Tests exams here. Each question offers a chance to enhance your knowledge regarding Neural Networks.

Neural Networks Online Quiz

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Test Name: Neural Networks MCQ Quiz Practice
Type: Quiz Test
Total Questions: 40
Total Marks: 40
Time: 40 minutes

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Neural Networks Quiz

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1 / 40

Which of the following is a common optimization algorithm used for training Neural Networks?

Adam

Decision Tree

K-Means

2 / 40

The process of adjusting the weights and biases of a Neural Network to minimize error is known as ___________.

Activation

Training

Testing

3 / 40

Which of the following is used to initialize the weights of a Neural Network?

He initialization

Zero initialization

Random initialization

4 / 40

Which Neural Network architecture is suitable for processing sequences of data?

Convolutional Neural Network (CNN)

Autoencoder

Recurrent Neural Network (RNN)

5 / 40

Which of the following is a technique used to train Neural Networks on multiple GPUs or machines?

Data parallelism

Task parallelism

Model parallelism

6 / 40

Which of the following is a drawback of using a deep Neural Network?

Computationally expensive

Prone to underfitting

Limited expressiveness

7 / 40

Which type of Neural Network is used for anomaly detection in data?

Recurrent Neural Network (RNN)

Multilayer Perceptron (MLP)

Autoencoder

8 / 40

Which type of Neural Network is used for learning continuous representations of data?

Self-Organizing Map (SOM)

Autoencoder

Generative Adversarial Network (GAN)

9 / 40

In a feedforward Neural Network, connections between nodes do not form ____________.

Branches

Cycles

Loops

10 / 40

Which layer of a Neural Network typically follows a convolutional layer in a CNN?

Activation

Fully Connected

Pooling

11 / 40

Which of the following is a technique to visualize the learned features in a Convolutional Neural Network (CNN)?

Gradient visualization

Filters visualization

Activation visualization

12 / 40

Which of the following is a disadvantage of using a shallow Neural Network compared to a deep Neural Network?

Limited learning capacity

Longer training time

More prone to overfitting

13 / 40

The ___________ layer in a Neural Network is responsible for making predictions.

Output

Input

Hidden

14 / 40

Which Neural Network architecture is often used for generating new data similar to the training data?

Generative Adversarial Network (GAN)

Autoencoder

Recurrent Neural Network (RNN)

15 / 40

Which of the following is a common use case of Convolutional Neural Networks (CNNs)?

Sentiment Analysis

Image Classification

Time Series Prediction

16 / 40

Which of the following is used to prevent overfitting in a Neural Network?

Batch Normalization

Dropout

Max Pooling

17 / 40

Which of the following is a hyperparameter of a Neural Network?

Learning Rate

Activation

Weight

18 / 40

Which type of Neural Network is known for its ability to approximate any continuous function?

Convolutional Neural Network (CNN)

Multilayer Perceptron (MLP)

Recurrent Neural Network (RNN)

19 / 40

Which activation function is commonly used in the output layer of a binary classification Neural Network?

Sigmoid

Tanh

ReLU

20 / 40

Which type of Neural Network is used for unsupervised learning of efficient codings of input data?

Autoencoder

Multilayer Perceptron (MLP)

Convolutional Neural Network (CNN)

21 / 40

Which of the following is a technique to visualize the activations of different layers in a Neural Network?

Backpropagation

Activation Maximization

Gradient Descent

22 / 40

Which type of Neural Network is specifically designed for processing sequential data?

Multilayer Perceptron (MLP)

Autoencoder

Recurrent Neural Network (RNN)

23 / 40

Which of the following activation functions is linear?

Identity

Sigmoid

ReLU

24 / 40

What is the primary purpose of the dropout technique in a Neural Network?

Preventing local minima

Accelerating training

Regularization

25 / 40

What is the purpose of the softmax function in a Neural Network?

Convert raw scores into probabilities

Reduce computational complexity

Improve convergence speed

26 / 40

Which layer of a Neural Network is responsible for combining features learned by previous layers?

Fully Connected

Pooling

Convolutional

27 / 40

Which activation function is commonly used in the hidden layers of a Neural Network?

Sigmoid

Tanh

ReLU

28 / 40

What is the purpose of the learning rate in training a Neural Network?

Determine the number of hidden layers

Define the number of training epochs

Control the step size of weight updates

29 / 40

Which activation function is most commonly used in the output layer of a regression Neural Network?

Linear

Sigmoid

Tanh

30 / 40

Which of the following is a common method to deal with imbalanced datasets in Neural Networks?

Oversampling

Undersampling

Both

31 / 40

What is the purpose of the bias term in a Neural Network?

Prevent overfitting

Provide additional capacity

Shift the activation function

32 / 40

Which layer of a Neural Network is responsible for reducing the dimensionality of the input data?

Pooling

Dense

Convolutional

33 / 40

The process of evaluating a trained Neural Network on unseen data is known as ___________.

Testing

Inference

Validation

34 / 40

Which of the following is a common method to address vanishing gradients in deep Neural Networks?

Using skip connections

Using L1 regularization

Using ReLU activation

35 / 40

Which type of Neural Network is commonly used for image generation tasks?

Recurrent Neural Network (RNN)

Generative Adversarial Network (GAN)

Autoencoder

36 / 40

Which of the following is not a type of Neural Network?

Recurrent Neural Network (RNN)

Deep Belief Network (DBN)

Convolutional Neural Network (CNN)

37 / 40

Which of the following is a common application of a Self-Organizing Map (SOM)?

Clustering

Image Classification

Reinforcement Learning

38 / 40

In a Neural Network, weights and biases are updated using which algorithm?

Backpropagation

Gradient Descent

K-Means

39 / 40

Which of the following is a disadvantage of using a large batch size in training a Neural Network?

Increased generalization

Slower convergence

Higher memory requirement

40 / 40

Which type of Neural Network is capable of learning from past experiences and has memory?

Recurrent Neural Network (RNN)

Convolutional Neural Network (CNN)

Multilayer Perceptron (MLP)

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Computer MCQs 360April 10, 2024

0 12 1 minute read