Practice - NLP Pipeline Overview
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Practice Questions
Test your understanding with targeted questions
What is tokenization in NLP?
💡 Hint: Think about how we prepare text for analysis.
What are stopwords?
💡 Hint: Consider words that are frequently used in English.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What is the first step in the NLP pipeline?
💡 Hint: Think about how we clean text before we process it.
True or False: Stemming considers the context of a word when reducing it to its root form.
💡 Hint: Think about how 'running' might be treated differently in stemming versus lemmatization.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Using an example, explain how stemming and lemmatization would differ on the word 'better'.
💡 Hint: Consider which method looks at context.
Discuss in detail how TF-IDF could be applied to rank documents for a query. Provide a brief use case.
💡 Hint: Think about the relationship between document relevance and terms.
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Reference links
Supplementary resources to enhance your learning experience.
- Introduction to Natural Language Processing
- Tokenization in NLP
- Understanding TF-IDF for Text Mining
- Word2Vec Explained by Chris Olah
- Introduction to Word Embeddings
- Support Vector Machines for Beginners
- Understanding BERT
- Named Entity Recognition with NLTK
- Comprehensive Guide to LSTM
- Machine Translation: An Overview