Muhammad Imdad Ullah

Challenge your understanding of Neural Network MCQs, deep learning, and AI systems with this expertly crafted Multiple-Choice Quiz. Designed for students, researchers, data scientists, and machine learning engineers, this quiz covers essential topics such as:

• RNNs & LSTMs (architecture, components, and common misconceptions)
• Biological vs. Artificial Neurons (similarities and key differences)
• Binary Classification (MLPs, activation functions, and loss functions)
• Data Preprocessing & Model Deployment (real-world applications like house price prediction and medical diagnosis)
• AI Milestones (Deep Blue vs. AlphaGo)

Perfect for exam preparation, job interviews, and self-assessment, this quiz helps you:

• Identify gaps in neural network fundamentals
• Strengthen knowledge of deep learning architectures
• Apply concepts to real-world data science problems

Ideal for: University exams, data science certifications, AI/ML interviews, and self-study. Let us start with Online Neural Network MCQs with Answers now.

Online Neural Network MCQs with Answers

1. Which of the following is NOT a common activation function?

 Tanh

 Softmax

 Gradient Descent

 Sigmoid

 ReLU

2. Which of the following are benefits of using a multilayer perceptron neural network for binary classification?

 Requires less computational power

 Ability to handle non-linear relationships

 Scalability to large datasets

 High interpretability of the model’s decisions

 Flexibility in architecture design

3. Which loss function is commonly used for binary classification problems?

 Huber Loss

 Mean Squared Error (MSE)

 Hinge Loss

 Cross-Entropy Loss

4. How can a trained model be utilized to predict the price of a house based on input data?

 By using the input data to retrain the model

 By averaging the input data values

 By passing the input data through the model’s prediction function

 By normalizing the input data and directly mapping it to prices

5. Which of the following is an example of a data science application?

 Recommendation engine

 Mimic the human brain

 Data storage

 Spreadsheets

6. What is the primary purpose of a multilayer perceptron neural network in binary classification?

 To reduce the dimensionality of input data

 To categorize input data into one of two classes

 To cluster data into multiple groups

 To generate continuous values from input data

7. Among the following descriptions on RNNs (Recurrent Neural Networks), which is incorrect?

 In RNN S2S (Sequence to Sequence) operations, N inputs are transformed into M outputs, where M has to be always a larger number than N

 Self-Loop in the LSTM cell gives a data sequence memory effect

 In representation with attention, the attention values represent the importance of the corresponding data

 In FRNN (Fully Recurrent NN), the input, hidden, and output layer neurons have connections to all other neurons with modifiable weights

8. Which of the following steps are involved in creating a multilayer perceptron neural network for binary classification?

 Selecting an appropriate activation function

 Using a dimensionality reduction technique

 Applying a clustering algorithm

 Initializing weights and biases

 Choosing a loss function suitable for binary classification

9. What is the role of the learning rate in training a neural network?

 It controls how much weights are updated during backpropagation

 It selects the best activation function

 It determines the number of layers in the network

 It defines the number of training epochs

10. What are some common preprocessing steps for input data in a house price prediction model?

 Encoding categorical variables

 Normalizing or standardizing the data

 Adding noise to the data

 Handling missing values

 Randomly shuffling the data

11. Neural networks have been around for decades, but due to religious reasons, people decided not to develop them anymore because a neural network mimics the brain in the way it learns data.

 True

 False

12. Among the representation techniques used in RNNs (Recurrent Neural Networks), which is incorrect?

 Representation in RNNs is applied to the output layer data

 Representation is used to extract the important data that characterizes the data set in the best way

 Representation is a non-linear down-sampling process

 SoftMax is a very popular representation with attention method

13. Select the characteristics that are shared by both biological neural networks and artificial neural networks.

 Functioning without any form of energy

 Operation based on binary code

 Use of synaptic connections

 Ability to learn from data

 Reproduction of new neurons automatically

14. Among the following system components, which is not commonly used in an LSTM (Long Short-Term Memory) cell?

 Self-Loop

 Input Gate

 Output Gate

 Forget Gate

 Convolution Gate

15. What is the primary function of an activation function in a neural network?

 To introduce non-linearity into the network

 To optimize weight updates

 To reduce computation time

 To normalize input data

16. Which activation function is commonly used in the output layer of a binary classification neural network?

 ReLU function

 Softmax function

 Sigmoid function

 Tanh function

17. In the context of predicting heart disease, what does binary classification aim to achieve?

 Identifying the specific type of heart disease

 Distinguishing between patients with and without heart disease

 Assigning a risk score to each patient

 Predicting the progression of heart disease over time

18. How do artificial neurons typically differ from biological neurons?

 Artificial neurons can reproduce, but biological neurons cannot

 Artificial neurons are slower than biological neurons

 Artificial neurons do not require energy, but biological neurons do

 Artificial neurons use mathematical functions while biological neurons use electrochemical signals

19. Among the following descriptions of IBM’s Deep Blue and Google’s AlphaGo, which is incorrect?

 In 2016, Google’s AlphaGo competed against IBM’s Deep Blue in a Go game and won the match

 In matches held during 1996 to 1997, IBM’s Deep Blue beat the world’s top ranked Chess players

 After 1997, the CCRL (Computer Chess Rating Lists) for computers was made separately from the FIDE World Chess Federation Ratings for humans (e.g., chess Grand Masters)

 From 2015 to 2017, Google’s AlphaGo beats the world’s top ranking Go players

 In matches held during 1996 to 1997, IBM’s Deep Blue beat the world’s top ranked Chess players

20. What is the correct process for converting input data into an array for a house price prediction model?

 Manually type each data point into an array

 Write a custom script to convert the data into an array

 Use a library function to read the data and convert it to an array

 Convert the data to an array using a spreadsheet software

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Online Neural Network MCQs with Answers

• Among the following descriptions of IBM’s Deep Blue and Google’s AlphaGo, which is incorrect?
• Among the representation techniques used in RNNs (Recurrent Neural Networks), which is incorrect?
• Among the following system components, which is not commonly used in an LSTM (Long Short-Term Memory) cell?
• Among the following descriptions on RNNs (Recurrent Neural Networks), which is incorrect?
• How do artificial neurons typically differ from biological neurons?
• Select the characteristics that are shared by both biological neural networks and artificial neural networks.
• What is the correct process for converting input data into an array for a house price prediction model?
• What is the primary purpose of a multilayer perceptron neural network in binary classification?
• Which of the following are benefits of using a multilayer perceptron neural network for binary classification?
• What are some common preprocessing steps for input data in a house price prediction model?
• How can a trained model be utilized to predict the price of a house based on input data?
• In the context of predicting heart disease, what does binary classification aim to achieve?
• Which activation function is commonly used in the output layer of a binary classification neural network?
• Which of the following steps are involved in creating a multilayer perceptron neural network for binary classification?
• Neural networks have been around for decades, but due to religious reasons, people decided not to develop them anymore because a neural network mimics the brain in the way it learns data.
• Which of the following is an example of a data science application?
• What is the primary function of an activation function in a neural network?
• Which of the following is NOT a common activation function?
• Which loss function is commonly used for binary classification problems?
• What is the role of the learning rate in training a neural network?

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