9.4 - Feature Extraction Techniques
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 is the primary focus of the Bag of Words model?
💡 Hint: Think about how the model treats words in a document.
Name one advantage of TF-IDF over Bag of Words.
💡 Hint: Consider how it weights terms.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
Which technique focuses on word frequency count and ignores word order?
💡 Hint: Think of a simple counting approach.
True or False: TF-IDF gives higher weights to common words across a document.
💡 Hint: Consider the meaning of 'inverse' in IDF.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Design a simple document similarity algorithm using Bag of Words and explain how you would implement it.
💡 Hint: Think about vector mathematics for similarity.
Functionally assess the application of FastText in an NLP system that handles diverse languages - what are the pros and cons?
💡 Hint: Consider context and different language structures.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.