Practice Feature Engineering - 1.2.3 | Chapter 6: AI and Machine Learning in IoT | IoT (Internet of Things) Advance
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1.2.3 - Feature Engineering

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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is feature engineering?

💡 Hint: Think about the steps involved in shaping data for analysis.

Question 2

Easy

Why is normalization important in data preprocessing?

💡 Hint: Consider how varying ranges might affect model learning.

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 main goal of feature engineering?

  • To clean data
  • To create new features
  • To improve model performance

💡 Hint: Consider how this impacts the accuracy of predictions.

Question 2

True or False: Normalization is unnecessary if all input features are already on the same scale.

  • True
  • False

💡 Hint: Remember how features interact within the model.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You are given a dataset from a smart factory showcasing machine temperatures over a month. Describe how you would apply feature engineering techniques to prepare this dataset for a predictive maintenance model.

💡 Hint: Think systematically about each step in the feature engineering process.

Question 2

Design a method for a continuous monitoring system in a smart home that captures concept drift and updates its model accordingly.

💡 Hint: Consider the iterative nature of monitoring and updating.

Challenge and get performance evaluation