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4 cards from this section. Quick, good the night before a test.
What is a loss function?
Think about what you need to check if your guesses are correct.
Give an example of a common loss function used in regression.
Remember it involves squaring errors.
What does the loss function measure?
Think about what you want to measure when checking predictions.
Cross Entropy is primarily used in which type of task?
Consider what kind of problems you'd use probabilities for.
Given a dataset with predicted values [4, 5, 6] and actual values [5, 5, 5], calculate the Mean Squared Error.
Square the differences first, then average.
In a binary classification task, if the model predicts probabilities as [0.9, 0.2] for two samples and the actual outputs are [1, 0], calculate the Cross Entropy loss.
Use the formula for computing Cross Entropy based on the actual labels and predicted probabilities.
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