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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the purpose of data preprocessing?
💡 Hint: Think about why raw data can't be used directly.
Question 2
Easy
Name one technique used in noise filtering.
💡 Hint: Consider what could cause errors in sensor data.
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 is the primary goal of data preprocessing?
- To analyze raw data
- To clean and prepare data for analysis
- To collect more data
💡 Hint: Remember the steps involved in preparing data.
Question 2
Does normalization help in ensuring each feature contributes equally during training?
- True
- False
💡 Hint: Consider how data ranges might affect a model's performance.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You have temperature data collected from a factory machine but it's littered with outliers and gaps. Describe a strategy to preprocess this data effectively.
💡 Hint: Think about what each step you learned does.
Question 2
Design a machine learning model’s preprocessing pipeline for predictive maintenance using IoT data. Include each preprocessing step and justify its importance.
💡 Hint: Consider the factors affecting machine failure and how you'd detect them.
Challenge and get performance evaluation