Neural Networks Fundamentals for Competitive Exam Prep

Neural Networks Fundamentals - Numerical Applications

Q. In a neural network, what does the term 'backpropagation' refer to?

Solution

Backpropagation is the algorithm used to update the weights of the network by calculating the gradient of the loss function.

Correct Answer: B — The method of updating weights based on error

Q. In which scenario would you typically use a Convolutional Neural Network (CNN)?

Solution

CNNs are specifically designed for processing structured grid data like images, making them ideal for image classification tasks.

Correct Answer: B — Image classification

Q. What does the term 'learning rate' control in a neural network?

Solution

The learning rate determines how much to change the model in response to the estimated error each time the model weights are updated.

Correct Answer: B — The speed of weight updates

Q. What is the purpose of normalization in the context of neural networks?

Solution

Normalization helps to ensure that all input features contribute equally to the model's learning process by scaling them to a similar range.

Correct Answer: B — To ensure all input features have similar scales

Q. Which evaluation metric is commonly used for classification tasks in neural networks?

Solution

Accuracy is a common metric used to evaluate the performance of classification models, including neural networks.

Correct Answer: B — Accuracy

Q. Which metric is commonly used to evaluate the performance of a neural network on a classification task?

Solution

Accuracy is a common metric for evaluating classification models, indicating the proportion of correct predictions.

Correct Answer: B — Accuracy

Q. Which of the following is a common application of neural networks?

Solution

Neural networks are widely used in image recognition tasks due to their ability to learn complex patterns in visual data.

Correct Answer: A — Image recognition

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