Practice Supervised Learning (6.2.1) - Machine Learning Basics - AI Course Fundamental

Practice: Supervised Learning

Lesson 6.2.1Machine Learning Basics

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8 questions

Flashcard drill
4 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
2 questions · about 1 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
Define supervised learning in your own words.
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Think about what it means to have labels in a dataset.
Question 2.
What is the goal of classification tasks in supervised learning?
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Remember the types of outcomes we want from classification.
3Question 3.
What is the main difference between supervised and unsupervised learning?
- Supervised learning uses labeled data
- Unsupervised learning uses labeled data
- They are the same
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Think about how they handle the data!
4Question 4.
True or False: Regression is a type of classification.
- True
- False
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Recall the definitions of each task.
Question 5.
Develop a simple supervised learning model for predicting student grades based on hours studied and class attendance.
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Consider how each input might influence grades.
Question 6.
Evaluate the effectiveness of using a Decision Tree versus Logistic Regression on a dataset containing health metrics to predict diabetes presence.
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Think about the nature of your data: categorical versus numerical outputs.

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