Complete tutorial on Text Classification using Conditional Random Fields Model (in Python)
Introduction
The amount of text data being generated in the world is staggering. Google processes more than 40,000 searches EVERY second! According to a Forbes report, every single minute we send 16 million text messages and post 510,00 comments on Facebook. For a layman, it is difficult to even grasp the sheer magnitude of data out there?
News sites and other online media alone generate tons of text content on an hourly basis. Analyzing patterns in that data can become daunting if you don’t have the right tools. Here we will discuss one such approach, using entity recognition, called Conditional Random Fields (CRF).
This article explains the concept and python implementation of conditional random fields on a self-annotated dataset. This is a really fun concept and I’m sure you’ll enjoy taking this ride with me!
Table of contents
- What is Entity Recognition?
- Case Study Objective and Understanding Different Approaches
- Formulating Conditional