NLP with Tidytext R
48mAdvanced2023-05-18
Authors
Mark Niemann-Ross
Technologist experienced in hardware, software, and science fiction
Course details
Natural language processing (NLP) is one of the hottest topics in tech. It works with words the same way computer vision works with pictures, delivering impressive analytic results. In this course, instructor Mark Niemann-Ross shows you how to get started implementing NLP algorithms using tidytext, a text mining tool package designed uniquely for the R programming language. Find out why R is so perfectly adept for manipulating matrices, producing statistics, and performing other related NLP tasks, such as calculating term frequency, tokenizing, punctuating, stemming and lemmatization, sentiment analysis, and more.
Skills covered
RStatisticsNatural Language Processing (NLP)AdvancedArtificial Intelligence (AI)Programming LanguagesData ScienceOpen SourceSoftware Development
Concepts
Introduction
- Welcome to natural language processing (NLP) with R
- Skills you need to be successful in this course
Use of Tidytext for NLP
- How to think like tidytext
- An example - Calculate the most popular terms in a document
- Tokenizing with unnest tokens()
- Stopwords, punctuation, whitespace, and numbers
- Stemming and lemmatization
- Term frequency with bind tf idf()
- Sentiment analysis with sentiments()
- Parts of speech with parts of speech()
- Import and export from other NLP packages
Conclusion
- Next steps