A Gentle Introduction to the Bag-of-Words Model
Last Updated on August 7, 2019
The bag-of-words model is a way of representing text data when modeling text with machine learning algorithms.
The bag-of-words model is simple to understand and implement and has seen great success in problems such as language modeling and document classification.
In this tutorial, you will discover the bag-of-words model for feature extraction in natural language processing.
After completing this tutorial, you will know:
- What the bag-of-words model is and why it is needed to represent text.
- How to develop a bag-of-words model for a collection of documents.
- How to use different techniques to prepare a vocabulary and score words.
Kick-start your project with my new book Deep Learning for Natural Language Processing, including step-by-step tutorials and the Python source code files for all examples.
Let’s get started.
A Gentle Introduction to the Bag-of-Words Model
Photo by Do8y, some rights reserved.
Tutorial Overview
This tutorial is divided into 6 parts; they are:
- The Problem with Text
- What is a Bag-of-Words?
- Example of the
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