Practice Chapter Summary - 6.4 | 6. Unsupervised Learning – Clustering & Dimensionality Reduction | Data Science Advance
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Chapter Summary

6.4 - Chapter Summary

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is unsupervised learning?

💡 Hint: Think about learning without any guidance or answers.

Question 2 Easy

Give an example of a clustering algorithm.

💡 Hint: What methods group similar points together?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does unsupervised learning focus on?

Labeled data
Finding patterns
Classification

💡 Hint: Think about what you can discover without guidance.

Question 2

True or False: DBSCAN requires you to pre-define the number of clusters.

True
False

💡 Hint: Reflect on its ability to detect dense regions.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

If you have a dataset with varying densities across clusters, how might you select the appropriate clustering algorithm?

💡 Hint: Reflect on the sensitivity of algorithms to density.

Challenge 2 Hard

You use PCA on a dataset, but the results are hard to interpret. What could you do to improve interpretation?

💡 Hint: Think about visualization techniques that help make complex data understandable.

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