Practice Natural Language Processing (NLP) - 9 | 9. Natural Language Processing (NLP) | Data Science Advance
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Natural Language Processing (NLP)

9 - Natural Language Processing (NLP)

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is tokenization?

💡 Hint: Think about how we break a sentence into its individual components.

Question 2 Easy

What does NLP stand for?

💡 Hint: Recall the full form based on the acronym.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does NLP enable machines to do?

Understand human emotions
Comprehend and generate human language
Perform complex mathematics

💡 Hint: Remember the core goals of NLP.

Question 2

True or False: Stemming ignores the context of words when reducing them.

True
False

💡 Hint: Think about how stemming differs from lemmatization.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You have a dataset of customer reviews. Outline an NLP pipeline you would use to classify these reviews as positive or negative.

💡 Hint: Consider each step carefully and how they add up to form a complete process.

Challenge 2 Hard

Critique the limitations of the Bag of Words model compared to Word Embeddings.

💡 Hint: Focus on how each model approaches complex meanings differently.

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Reference links

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