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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does SVM stand for, and in which application is it used?
💡 Hint: Focus on the acronym and its primary use.
Question 2
Easy
Explain what k-NN is used for in recommendation systems.
💡 Hint: Consider how k-NN assesses user preferences.
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 one application of SVMs?
- Handwriting Recognition
- Linear Regression
- Clustering
💡 Hint: Think about how characters are usually classified.
Question 2
True or False: k-NN is a non-parametric method used for classification.
- True
- False
💡 Hint: Recall the definition of non-parametric methods.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a dataset with unknown distributions, how would you approach using k-NN for classification?
💡 Hint: Think about the importance of distance metrics and normalization in k-NN.
Question 2
Discuss how decision trees manage the trade-off between bias and variance in a given dataset.
💡 Hint: Reflect on how reducing complexity affects bias and variance in models.
Challenge and get performance evaluation