9.2.1 - Text Preprocessing
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 tokenization?
💡 Hint: What do we do to make text easier to analyze?
Give an example of a stop-word.
💡 Hint: What are some common words that we often remove in analysis?
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What does tokenization accomplish?
💡 Hint: Think about what helps us to analyze sentences.
True or False: Stop-words are always removed from all textual data.
💡 Hint: Think about literature and forms of expression.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
Given the sentence: 'The quick brown fox jumps over the lazy dog.' tokenize it and identify the stop-words.
💡 Hint: Look for common words that don’t add meaning.
In what scenarios might lemmatization be more beneficial than stemming? Provide at least two examples.
💡 Hint: Consider tasks where word meaning is crucial.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.