MCQ IN COMPUTER SCIENCE & ENGINEERING

COMPUTER SCIENCE AND ENGINEERING

MACHINE LEARNING

Question [CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
What is the typical pipeline for a classification model using text data?
A
vectorize text > normalize text > train model > deploy model
B
train model > normalize text > vectorize text > deploy model
C
normalize text > vectorize text > deploy model > train model
D
normalize text > vectorize text > train model > deploy model
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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