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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is a loss function?
💡 Hint: Think about what you need to check if your guesses are correct.
Question 2
Easy
Give an example of a common loss function used in regression.
💡 Hint: Remember it involves squaring errors.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does the loss function measure?
- Accuracy of predictions
- Difference between predicted and actual output
- Speed of model training
💡 Hint: Think about what you want to measure when checking predictions.
Question 2
Cross Entropy is primarily used in which type of task?
- Classification
- Regression
- Clustering
💡 Hint: Consider what kind of problems you'd use probabilities for.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a dataset with predicted values [4, 5, 6] and actual values [5, 5, 5], calculate the Mean Squared Error.
💡 Hint: Square the differences first, then average.
Question 2
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.
💡 Hint: Use the formula for computing Cross Entropy based on the actual labels and predicted probabilities.
Challenge and get performance evaluation