NLP Basics

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Tokenization in Natural Language Processing

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Tokenization is the process of breaking down text into smaller units called tokens.

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Part-of-Speech Tagging

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Part-of-Speech Tagging is the process of assigning a part of speech to each word in a given text based on its definition and context.

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How is Sentiment Analysis used in NLP?

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Sentiment Analysis is used in NLP to determine the emotional tone behind text data.

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Explain the concept of cosine similarity in NLP.

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Cosine similarity is a measure used to determine how similar two documents are based on their word frequencies. It calculates the cosine of the angle between two vectors in a multi-dimensional space.

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What is TF-IDF and how is it used in NLP?

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TF-IDF is a numerical statistic used in NLP to determine the importance of a word in a document relative to a collection of documents by multiplying the term frequency (TF) of a word in a document by the inverse document frequency (IDF) of the word across the entire corpus.

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Which of the following tasks is NOT a typical NLP application? Speech recognition, Image classification, Machine translation, Sentiment analysis

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Image classification

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Which technique is used to reduce words to their base or root form in NLP?

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Stemming

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Which Python library is commonly used for NLP tasks such as stemming and lemmatization? Options: Matplotlib, Scikit-learn, NLTK, Pandas

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NLTK

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What is the primary difference between stemming and lemmatization?

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Stemming removes suffixes, while lemmatization considers the context and reduces words to their base or dictionary form

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What is the main difference between simple counting techniques (like Bag of Words) and TF-IDF in text analysis?

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Counting techniques only count the frequency of terms in a document, while TF-IDF also considers the importance of terms across the entire corpus.