SOFT COMPUTING

1. What is a Neural Network?

a) A computational model inspired by the human brain. b) A type of database management system. c) A programming language for AI. d) A hardware component used in robotics.

2. What is the basic building block of a Neural Network?

a) Neuron. b) Layer. c) Algorithm. d) Dataset.

3. What is the role of an "activation function" in a Neural Network?

a) To determine the output of a neuron. b) To store the input data. c) To initialize the weights. d) To visualize the results.

4. What is the purpose of the "hidden layer" in a Neural Network?

a) To process and transform input data into a more useful representation. b) To store the input data. c) To display the final output. d) To connect the network to external devices.

5. Which of the following is a common activation function used in Neural Networks?

a) ReLU (Rectified Linear Unit). b) SQL (Structured Query Language). c) HTML (HyperText Markup Language). d) JPEG (Joint Photographic Experts Group).

6. What is "backpropagation" in Neural Networks?

a) A method to initialize weights in the network. b) A technique to adjust weights based on the error in predictions. c) A process to visualize data. d) A type of hardware used in Neural Networks.

7. What is the role of "weights" in a Neural Network?

a) They store the input data. b) They determine the strength of the connection between neurons. c) They are used to display the output. d) They are used to connect the network to the internet.

8. Which of the following is a type of Neural Network?

a) Convolutional Neural Network (CNN). b) Random Forest. c) Decision Tree. d) K-Means Clustering.

9. What is "overfitting" in the context of Neural Networks?

a) When the model performs well on training data but poorly on unseen data. b) When the model is too simple to capture patterns in the data. c) When the model stops learning. d) When the model runs out of memory.

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

a) It controls the speed at which the model learns. b) It determines the number of layers in the network. c) It is used to store the training data. d) It is used to visualize the output.

Neural Network Concepts MCQs

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