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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is supervised learning?
💡 Hint: Think about how the model learns from examples.
Question 2
Easy
What are input features?
💡 Hint: These are the things we provide to the model to make a prediction.
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 defines supervised learning?
- Training on unlabeled data
- Training on labeled data
- Training without a defined output
💡 Hint: Think about what the model needs to learn effectively.
Question 2
True or False: In supervised learning, the model can make predictions without any input features.
- True
- False
💡 Hint: What do you need to provide for the model to learn?
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a simple supervised learning model for predicting the number of sales based on advertising expenditure. Outline the steps you would take.
💡 Hint: Think about what inputs would serve as effective predictors for sales.
Question 2
Explain why choosing a supervised learning model might not be effective in the case of predicting customer behavior in a new marketplace without historical data.
💡 Hint: Consider the role of past data in making predictions.
Challenge and get performance evaluation