Practice Unsupervised Learning (30.3.2.b) - Introduction to Machine Learning and AI

Practice: Unsupervised Learning

Lesson 30.3.2.bIntroduction to Machine Learning and AI

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9 questions

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6 sample questions

Question 1.
Define unsupervised learning in your own words.
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Think about what it means to learn without guidance.
Question 2.
What is a common use for clustering?
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Consider categories you encounter in everyday life.
3Question 3.
What does unsupervised learning aim to accomplish?
- A) Identify labels for data
- B) Discover hidden patterns in data
- C) Predict outcomes using labeled data
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Think about what you can uncover without explicit guidance.
4Question 4.
True or false: K-Means is a supervised learning algorithm.
- True
- False
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Recall the definitions of supervised and unsupervised learning.
Question 5.
Design an unsupervised learning project for analyzing urban traffic patterns. What data would you collect, and which algorithm would you choose?
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Think about how traffic flows vary across different times and locations.
Question 6.
Evaluate the effectiveness of using Hierarchical Clustering versus K-Means in grouping renovation project types. What factors would influence your choice?
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Consider the dataset size and the need for visual representation.

5 more questions in this section. Enroll free to practise them all.