2.5.1 - Feature Extraction
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Practice Questions
Test your understanding with targeted questions
What does feature extraction do?
💡 Hint: Think about transforming raw data.
Name a technique used in feature extraction for text data.
💡 Hint: What method evaluates word importance?
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What is feature extraction?
💡 Hint: Think about the purpose of transforming data in ML.
TF-IDF stands for what?
💡 Hint: Remember it evaluates word importance.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Draft a complete feature extraction plan for a dataset containing user activities on a website, specifying which features to extract and the techniques to use.
💡 Hint: Think about what information would be most relevant for analyzing user behavior.
Analyze the pros and cons of using feature extraction methods like TF-IDF and Bag of Words in a machine learning pipeline.
💡 Hint: Consider performance and outcome versus complexity.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.