This document discusses using Redis to perform text classification. It describes training a text classifier by counting words for different labels and categories. For classification, it stems, normalizes, and removes words from input text before calculating scores for each label based on the word counts. The Redis implementation stores initial labels and trained word counts in Sets and Hashes. It provides an API for training via POST requests with text and labels, and classifying text with POST requests that return the most likely label and confidence scores.