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Introduction to Text Classification in R with quanteda

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In this guided project you will learn how to import textual data stored in raw text files into R, turn these files into a corpus (a collection of textual documents), reshape them into paragraphs from documents and tokenize the text all using the R software package quanteda. You will then learn how to classify the texts using the Naive Bayes algorithm. This guided project is for beginners interested in quantitative text analysis in R. It assumes no knowledge of textual analysis and focuses on exploring textual data (US Presidential Concession Speeches). Users should have a basic understanding of the statistical programming language R.

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"Introduction to Text Classification in R with quanteda" is a foundational course in Data Science & AI, offered by Coursera. Taught by expert instructors, this 120-minute guided project teaches beginners how to import, tokenize, and classify textual data using the R package quanteda and the Naive Bayes algorithm. Ideal for those with a basic understanding of R, it focuses on quantitative text analysis, specifically using US Presidential Concession Speeches. Available with a Starter subscription, it's perfect for those new to textual analysis.