Practice - Module 4: Advanced Supervised Learning & Evaluation
Practice Questions
Test your understanding with targeted questions
What is ensemble learning?
💡 Hint: Think about how groups can make better decisions than individuals.
Name two types of ensemble methods.
💡 Hint: These methods can help improve model performance in machine learning.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the main advantage of ensemble learning?
💡 Hint: Think of how groups can reach a better conclusion than individuals.
True or False: Boosting builds models independently.
💡 Hint: Consider the sequential process of improvement.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
Analyze a dataset of credit scores and predict defaults using Random Forest. Discuss how you would evaluate the importance of features in the model.
💡 Hint: Consider how feature importance is typically computed in ensemble methods.
Consider a dataset with many misclassified records. How could you improve the baseline model accuracy using Boosting? Discuss the steps involved.
💡 Hint: Think about how error correction each round emphasizes learning from past mistakes.
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Reference links
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