Deep Learning Beginner Quiz 4
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Beginner Quiz 4
1. What is a convolutional neural network (CNN) mainly used for?
Analyzing images or visual data using learned filters
Sorting numerical values in spreadsheets only
Drafting and sending text-only email messages
2. What is a recurrent neural network (RNN) mainly used for?
Handling sequential data such as time series, text, or speech
Classifying still images with no temporal order
Providing long-term storage of training datasets
3. What is the main difference between deep learning and traditional machine learning?
Deep learning relies on multi-layer neural networks that learn features automatically
Deep learning can only operate on very tiny datasets
Deep learning models require no training phase at all
4. What is an example of an activation function?
ReLU, which outputs zero or a positive linear value
A plain summation operator over all inputs
A basic multiplication operation between two numbers
5. What is the output of a classification deep learning model?
One or more discrete labels representing predicted classes
A multi-sentence textual explanation of every input
A new dataset containing all raw input features
6. What is the output of a regression deep learning model?
A numeric value on a continuous scale, such as a price
A category name chosen from a fixed list
A full copy of the original training dataset
7. Which of these is a framework for building deep learning models?
Keras, which provides a high-level API for neural networks
Excel, which is used mainly for spreadsheets and charts
Word, which is used to edit and format documents
8. What is the main role of the optimizer in deep learning?
To adjust model parameters in order to minimize the loss function
To permanently store raw data and labels on disk
To automatically partition files into folders and subfolders
9. What is a simple way to prevent overfitting?
Collect more data, use regularization, or reduce model complexity
Continuously add more layers without any limit
Remove the prediction layer so the model has no output
10. What is the purpose of the softmax function?
To turn raw scores into a probability distribution over classes
To store all training examples in a single file
To split a dataset randomly into multiple folders
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