Introduction to Text Analytics with R - Overview

Dive into the world of text analytics with R programming in this introductory video series. Explore essential techniques including tokenization, stemming, n-grams, bag-of-words, and vector space models. Learn to engineer features for textual data, extract features using singular value decomposition, train classification models, and evaluate their accuracy. Begin with an overview of the spam dataset, data loading, initial cleaning, and preliminary analysis. Gain hands-on experience with R code and datasets provided, covering topics such as finding missing data, exploring text characteristics, and calculating text length. Prepare to harness the power of textual data in data science applications and products.

Introduction
About Dave
Housekeeping
Expectations
Data
Packages
Read CSV
Find missing data
Explore the data
Text Length