Test your knowledge of essential text preprocessing techniques in Natural Language Processing (NLP). This beginner-friendly quiz explores concepts like stop word removal, stemming algorithms (like Porter and Snowball), and lemmatization strategies using tools like NLTK and spaCy. Ideal for aspiring data scientists and NLP enthusiasts getting started with text cleaning and transformation.
Test your understanding of essential NLP preprocessing techniques, including Unicode normalization, case-folding, punctuation and whitespace handling, stopword removal, and word-frequency mapping. This quiz is designed to strengthen your knowledge of foundational steps in preparing text data for natural language processing tasks.
Test your understanding of building a basic keyword search engine with a hash-map-based inverted index. This quiz covers term-frequency counting, result sorting, pagination, and effective caching strategies for repeated queries.
Test your knowledge of tokenization, Unicode handling, casing, punctuation removal, and stopword filtering in text preprocessing. This quiz is designed to reinforce key concepts and methods essential for effective natural language processing workflows.
Test your knowledge of finding the top-K frequent words in a text corpus using hash maps and min-heaps. This quiz covers key concepts, usage scenarios, and time-space trade-offs in designing efficient solutions for word frequency analysis.