Practice Data Preprocessing (1.2) - Chapter 6: AI and Machine Learning in IoT

Practice: Data Preprocessing

Lesson 1.2AI and Machine Learning in IoT

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9 questions

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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
3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is the purpose of data preprocessing?
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Think about why raw data can't be used directly.
Question 2.
Name one technique used in noise filtering.
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Consider what could cause errors in sensor data.
3Question 3.
What is the primary goal of data preprocessing?
- To analyze raw data
- To clean and prepare data for analysis
- To collect more data
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Remember the steps involved in preparing data.
4Question 4.
Does normalization help in ensuring each feature contributes equally during training?
- True
- False
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Consider how data ranges might affect a model's performance.
Question 5.
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.
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Think about what each step you learned does.
Question 6.
Design a machine learning model’s preprocessing pipeline for predictive maintenance using IoT data. Include each preprocessing step and justify its importance.
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Consider the factors affecting machine failure and how you'd detect them.

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