Practice Tokenization (27.3.1) - Concepts of Natural Language Processing (NLP)
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Tokenization

Practice - Tokenization

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is tokenization?

💡 Hint: Think about how language can be divided into parts.

Question 2 Easy

Give an example of a token.

💡 Hint: Remember, it can be one word or a group of words.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main purpose of tokenization in NLP?

To break text into sentences
To process natural language efficiently
To generate text

💡 Hint: Focus on what enables better machine understanding.

Question 2

Tokenization is only important for word-level analysis. True or False?

True
False

💡 Hint: Remember its applications in both forms of text processing.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Explain how context can impact tokenization effects. Provide an example.

💡 Hint: Think about sentences where a word might have more than one interpretation.

Challenge 2 Hard

Design a simple tokenization function that differentiates between words and punctuation.

💡 Hint: Consider how regular expressions can help parse text effectively.

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