Practice Unsupervised Learning (6.2.2) - Machine Learning Basics - AI Course Fundamental

Practice: Unsupervised Learning

Lesson 6.2.2Machine Learning Basics

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9 questions

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Exercise
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Quiz
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6 sample questions

Question 1.
What is unsupervised learning?
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Think about how it differs from supervised learning.
Question 2.
Name one algorithm used in unsupervised learning.
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Consider types of algorithms that group data.
3Question 3.
What is the main goal of unsupervised learning?
- To classify data
- To find hidden patterns
- To reduce data noise
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Think about what the algorithm is trying to achieve without labels.
4Question 4.
True or False: K-Means clustering requires labeled data.
- True
- False
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Remember the definition of unsupervised learning.
Question 5.
Given a dataset of customer purchasing behavior without any labels, devise an approach using unsupervised learning to segment them into distinct marketing groups.
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Consider strategies for choosing the right number of clusters and how to interpret the results.
Question 6.
Imagine you have a large dataset of images where you want to reduce the number of features while retaining as much meaningful information as possible. Describe how you would use PCA in this scenario.
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Think about how dimensionality reduction affects data processing.

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