Processing Text with R Essential Training

Description

In this course, you will :

• Learn the fundamental techniques for cleansing and processing text in R, as well as how to convert text to a format suitable for analytics and predictions.
• begins with a review of text extraction, cleansing, and processing techniques.
• demonstrates how to convert text into an analytics-ready format, including the use of n-grams and TF-IDF
• provides examples of how to use the R and tm libraries to put these techniques to the test.

Syllabus :

1. Introduction to Text Mining

• Purpose
• Document
• Corpus
• R text processing libraries
• Setting up the environment

 

2. Corpus in R

• PCorpus and VCorpus
• Reading files with CorpusReader
• Exploring the corpus
• Persisting the corpus

 

3. Text Cleansing and Extraction

• Setup for processing
• Cleansing text
• Stop word removal
• Stemming
• Managing metadata

 

4. TF-IDF

• Introduction to tf-idf
• Generating term frequency matrix
• Improving term frequency matrix
• Plotting term frequency
• Generating tf-idf

 

5. N-Grams

• N-grams concepts
• Using RWeka NGramTokenizer
• Creating an n-gram text frequency matrix
• Extracting n-gram pairs

 

6. Best Practices

• Storing text
• Processing text data
• Scalability

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