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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is an objective function?
💡 Hint: Think of it as a measure of model performance.
Question 2
Easy
Name one loss function used in regression tasks.
💡 Hint: What do we measure in regression?
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 is an objective function?
- A function to maximize only
- A function to minimize only
- A function to either minimize or maximize
💡 Hint: Think about its role in optimization.
Question 2
True or False: Gradient Descent guarantees a global minimum in all cases.
- True
- False
💡 Hint: Consider the types of functions.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
An algorithm suffers from overfitting. How would you apply L1 or L2 regularization to mitigate this issue? Provide a practical coding example.
💡 Hint: Think about how regularization interacts with coefficients.
Question 2
You are tasked with optimizing a neural network with high variance in results. Discuss which hyperparameter tuning techniques could you implement and justify your choices.
💡 Hint: Consider how much time you can allocate for tuning.
Challenge and get performance evaluation