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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the purpose of data preprocessing?
π‘ Hint: Think about how data is prepared for machine learning models.
Question 2
Easy
Define the test set in a machine learning context.
π‘ Hint: Remember, it should not be used during training!
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is one purpose of data preprocessing?
π‘ Hint: Why do we clean and adjust the data before analysis?
Question 2
True or False: The test set should be used during model training.
π‘ Hint: Consider which data should guide the model's learning process.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
You have access to a dataset containing housing prices but find that several features contain missing values. Describe the steps you would take to prep this data for modeling, addressing missing values and potential outliers.
π‘ Hint: Consider the importance of each step and why it matters.
Question 2
Reflect on a scenario where your linear regression model shows high performance on training data but poor performance on test data. What steps would you consider to address this issue?
π‘ Hint: Think about potential causes and solutions systematically.
Challenge and get performance evaluation