1.2.3 - Feature Engineering
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Practice Questions
Test your understanding with targeted questions
What is feature engineering?
💡 Hint: Think about the steps involved in shaping data for analysis.
Why is normalization important in data preprocessing?
💡 Hint: Consider how varying ranges might affect model learning.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the main goal of feature engineering?
💡 Hint: Consider how this impacts the accuracy of predictions.
True or False: Normalization is unnecessary if all input features are already on the same scale.
💡 Hint: Remember how features interact within the model.
1 more question available
Challenge Problems
Push your limits with advanced challenges
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.
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.
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Reference links
Supplementary resources to enhance your learning experience.
- Feature Engineering for Machine Learning
- Understanding Feature Engineering in Machine Learning
- Noise Reduction Techniques
- How to Address Concept Drift
- Feature Engineering in Python
- Intro to Data Normalization
- TensorFlow Lite for Mobile Devices
- Creating a Moving Average in Excel
- Machine Learning Models Explained