Practice Expected Outcomes (6) - Unsupervised Learning & Dimensionality Reduction (Weeks 9)
Students

Academic Programs

AI-powered learning for grades 8-12, aligned with major curricula

Engineering Courses
Professional

Professional Courses

Industry-relevant training in Business, Technology, and Design

Certifications
Games

Interactive Games

Fun games to boost memory, math, typing, and English skills

Expected Outcomes

Practice - Expected Outcomes

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the function of K in K-Means Clustering?

💡 Hint: Think about how K relates to the clustering groups.

Question 2 Easy

What does the Elbow Method help us identify?

💡 Hint: Remember the visual aspect of this method.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is K-Means clustering primarily used for?

Supervised Learning
Clustering
Regression

💡 Hint: Think about how it groups data.

Question 2

True or False: DBSCAN requires you to specify the number of clusters in advance.

True
False

💡 Hint: Consider how DBSCAN forms clusters differently from K-Means.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You have a dataset with clear outlier points and uneven densities. Discuss how you would approach clustering and justify your choice of algorithm.

💡 Hint: Focus on the needs of your dataset.

Challenge 2 Hard

Explain a situation where the choice of K in K-Means could drastically affect the outcomes of clustering.

💡 Hint: Think about the dimensionality and distribution.

Get performance evaluation

Reference links

Supplementary resources to enhance your learning experience.