COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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What is the typical pipeline for a classification model using text data?
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vectorize text > normalize text > train model > deploy model
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train model > normalize text > vectorize text > deploy model
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normalize text > vectorize text > deploy model > train model
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normalize text > vectorize text > train model > deploy model
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Explanation:
Detailed explanation-1: -The six steps involved in NLP pipelines are-sentence segmentation, word tokenization, part of speech for each token. Text lemmatization, identifying stop words, and dependency parsing. Bio: Ram Tavva is Senior Data Scientist, Director at ExcelR Solutions.
Detailed explanation-2: -Some of the most popular text classification algorithms include the Naive Bayes family of algorithms, support vector machines (SVM), and deep learning.
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