Neural Networks MCQs December 22, 2025August 10, 2024 by u930973931_answers 30 min Score: 0 Attempted: 0/30 Subscribe 1. What is a neural network? (A) A framework for modeling complex relationships between inputs and outputs (B) A type of decision tree (C) A linear regression model (D) A clustering algorithm 2. Which of the following is the most basic unit in a neural network? (A) Epoch (B) Layer (C) Neuron (D) Bias 3. In a neural network, what does the term âepochâ refer to? (A) The number of hidden layers (B) The number of times the entire dataset is passed forward and backward through the neural network (C) The activation function used (D) The number of neurons in the input layer 4. Which of the following activation functions is commonly used in the output layer for binary classification tasks? (A) Sigmoid (B) ReLU (C) Tanh (D) Softmax 5. What is the purpose of the activation function in a neural network? (A) To reduce overfitting (B) To initialize weights (C) To introduce non-linearity into the model (D) To combine input features 6. Which of the following is a common problem when training deep neural networks? (A) Feature scaling (B) Vanishing gradients (C) Underfitting (D) Redundant weights 7. Which technique is often used to prevent overfitting in neural networks? (A) Regularization (B) Data augmentation (C) Dropout (D) All of the above 8. Which of the following is a typical characteristic of a deep neural network? (A) One output layer only (B) Multiple hidden layers (C) Use of k-means clustering (D) Linear relationships only 9. What is âbackpropagationâ in neural networks? (A) A process of adjusting weights in a neural network based on the error rate (B) A method of combining input features (C) A way to initialize weights (D) A data preprocessing technique 10. What is a âconvolutional neural networkâ (CNN) primarily used for? (A) Clustering (B) Time series forecasting (C) Text classification (D) Image and video recognition 11. Which of the following is a commonly used optimization algorithm in training neural networks? (A) Decision Tree (B) k-Nearest Neighbors (k-NN) (C) Stochastic Gradient Descent (SGD) (D) Naive Bayes 12. What is the purpose of the âsoftmaxâ function in the output layer of a neural network? (A) To reduce dimensionality (B) To initialize weights (C) To convert logits into probabilities (D) To standardize input features 13. Which of the following is true about the âReLUâ activation function? (A) It always outputs a value between 0 and 1 (B) It is used exclusively in the output layer (C) It is only applicable in regression tasks (D) It outputs zero for any negative input value 14. In a neural network, what does the term âbiasâ refer to? (A) The error term in the prediction (B) An extra parameter in the neuron used to adjust the output along with the weighted sum of inputs (C) The learning rate of the network (D) The difference between the predicted and actual output 15. What is âdropoutâ in the context of neural networks? (A) A type of activation function (B) A method for initializing weights (C) A regularization technique to prevent overfitting by randomly setting a fraction of neurons to zero during training (D) A preprocessing step for input data 16. Which of the following is a challenge in training very deep neural networks? (A) All of the above (B) Overfitting with too little data (C) Selecting an appropriate learning rate (D) Vanishing or exploding gradients 17. Which type of neural network is particularly well-suited for processing sequential data, such as time series? (A) Recurrent Neural Network (RNN) (B) Convolutional Neural Network (CNN) (C) Feedforward Neural Network (FNN) (D) Autoencoder 18. What is âweight initializationâ in neural networks? (A) The process of applying dropout (B) The final step in training a neural network (C) The process of tuning hyperparameters (D) The process of setting the initial values of weights before training begins 19. Which of the following describes a âfully connectedâ layer in a neural network? (A) The layer is only connected to the input layer (B) The layer contains only one neuron (C) The layer contains neurons with no activation functions (D) Every neuron in the layer is connected to every neuron in the previous and next layer 20. What does âLSTMâ stand for in the context of neural networks? (A) Logistic Simple Training Method (B) Linear Sequential Training Model (C) Least Squares Temporal Mapping (D) Long Short-Term Memory 21. What is the purpose of a âlearning rateâ in training a neural network? (A) To initialize the weights of the network (B) To set the number of neurons in each layer (C) To control the size of the steps the model takes during gradient descent (D) To determine the size of the training data 22. What is âgradient descentâ in the context of neural networks? (A) An optimization algorithm used to minimize the loss function (B) A type of activation function (C) A regularization technique (D) A method for data normalization 23. Which of the following is NOT a type of neural network? (A) Support Vector Machine (SVM) (B) Recurrent Neural Network (RNN) (C) Convolutional Neural Network (CNN) (D) Feedforward Neural Network (FNN) 24. Which of the following is true about âbatch normalizationâ? (A) It is only used in the output layer (B) It is used to prevent overfitting by randomly setting activations to zero (C) It is an activation function (D) It normalizes the input features of each mini-batch 25. In a neural network, what does the term âoverfittingâ refer to? (A) The model performs poorly on both training and test data (B) The model performs well on training data but poorly on unseen data (C) The model has too few parameters to capture the underlying patterns (D) The modelâs weights are not properly initialized 26. What is the purpose of using âdropoutâ during training? (A) To improve the accuracy of the model (B) To prevent overfitting by randomly dropping units during training (C) To speed up the training process (D) To enhance the regularization of the model 27. Which neural network architecture is best suited for natural language processing tasks? (A) Radial Basis Function Network (RBFN) (B) Convolutional Neural Network (CNN) (C) Feedforward Neural Network (FNN) (D) Recurrent Neural Network (RNN) 28. Which of the following is NOT a commonly used activation function? (A) Tanh (B) Softmax (C) AdaBoost (D) Linear 29. What is the role of âAdamâ optimizer in neural networks? (A) It is a type of activation function (B) It is an optimization algorithm used to adjust weights and biases (C) It is a method for weight initialization (D) It is used for data preprocessing 30. Which of the following describes âautoencodersâ? (A) Networks used exclusively for image classification (B) Networks used to process sequential data (C) Neural networks used for unsupervised learning to learn efficient representations of data (D) Networks used to detect anomalies in data