Performing Natural Language Processing with R
Intermediate
50 Lessons
9h
Certificate of Completion
Takeaway Skills
Working knowledge of natural language processing, including sentiment analysis, statistical analysis of corpus contents, and use of metadata
Hands-on experience with R natural language processing packages, including tidytext, tm, and quanteda
Familiarity with term frequency, stemming, n-grams, and lemmatization
Understanding of parts of speech and ability to apply it to natural language research
The ability to use tf-idf to identify documents corresponding with terms
Course Overview
This course will cover concepts in natural language processing (NLP). Developers will find this valuable because of the high demand for NLP skills. This includes understanding natural language when building applications like chatbots, sentiment analysis, search engines, and content recommendations. NLP also provides tools for data analysis, personalization, and content filtering. In this course, you will learn concepts of NLP, how to use the tm package, the use of corpora, how to convert text to structured...Show More
Course Content
Before We Begin
Important Concepts in Natural Language Processing
Text Mining Package
Understanding Corpora and Sources
Converting Text to Structured Data
Document Insights and Advanced Search Techniques
8 Lessons
Working with Metadata in the tm Package
4 Lessons
Implementing NLP with the quanteda Package
7 Lessons
Implementing NLP with the tidytext Package
7 Lessons
Assess What You Have Learned About NLP
Assessment
Concluding Remarks
1 Lesson
Appendix
1 Lesson
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