Natural Language Processing with Python Quick Start Guide

Example – text classification workflow

The preceding process is fairly generic. What would it look like for one of the most common natural language applications – text classification?

The following flow diagram was built by Microsoft Azure, and is used here to explain how their own technology fits directly into our workflow template. There are several new words that they have introduced to feature engineering, such as unigrams, TF-IDF, TF, n-grams, and so on:

The main steps in their flow diagram are as follows:

1. Step 1: Data preparation
2. Step 2: Text pre-processing
3. Step 3: Feature engineering:
   • Unigrams TF-IDF extraction
   • N-grams TF extraction ...