Practice Lab Objectives - 3.1 | Module 5: Unsupervised Learning & Dimensionality Reduction (Weeks 10) | Machine Learning
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does GMM stand for?

πŸ’‘ Hint: It involves the use of probability.

Question 2

Easy

What is the main goal of anomaly detection?

πŸ’‘ Hint: Think about what makes something unusual.

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 a primary advantage of GMMs over K-Means?

  • Handles elliptical clusters
  • Requires fewer data points
  • Is faster to compute

πŸ’‘ Hint: Think about the shapes these models can represent.

Question 2

Anomaly detection is primarily used to identify:

  • True
  • False

πŸ’‘ Hint: Consider the implications of detecting unusual occurrences.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a dataset with known clusters, apply GMM and compare its performance with K-Means. Discuss the findings.

πŸ’‘ Hint: Focus on cluster shapes and assignments.

Question 2

Design a basic framework using Isolation Forest on a dataset containing clear anomalies. Analyze its performance against a known set of anomalies.

πŸ’‘ Hint: Review how to tune parameters for optimal results.

Challenge and get performance evaluation