Practice Step 4: Model Building (18.3.4) - Data Science for Business and Decision- Making

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9 questions

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6 sample questions

Question 1.
What is supervised learning?
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Think about how a teacher guides a student.
Question 2.
Give one example of unsupervised learning.
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It's about discovering groups in data.
3Question 3.
Which method uses labeled data to train models?
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
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Think about the definition of the learning types.
4Question 4.
True or False: Unsupervised learning requires labeled training data.
- True
- False
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Reflect on the meaning of 'unsupervised'.
Question 5.
Design a supervised learning model for predicting loan defaults. What data would you collect, and what features would be most relevant?
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Think about attributes that indicate financial reliability.
Question 6.
Discuss how reinforcement learning can be implemented in a real-time bidding system for online advertising.
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Consider how learning from user interactions can influence decisions.

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