Book Image

fastText Quick Start Guide

By : Joydeep Bhattacharjee
Book Image

fastText Quick Start Guide

By: Joydeep Bhattacharjee

Overview of this book

Facebook's fastText library handles text representation and classification, used for Natural Language Processing (NLP). Most organizations have to deal with enormous amounts of text data on a daily basis, and gaining efficient data insights requires powerful NLP tools such as fastText.  This book is your ideal introduction to fastText. You will learn how to create fastText models from the command line, without the need for complicated code. You will explore the algorithms that fastText is built on and how to use them for word representation and text classification.  Next, you will use fastText in conjunction with other popular libraries and frameworks such as Keras, TensorFlow, and PyTorch.  Finally, you will deploy fastText models to mobile devices. By the end of this book, you will have all the required knowledge to use fastText in your own applications at work or in projects.
Table of Contents (14 chapters)
Free Chapter
First Steps
The FastText Model
Using FastText in Your Own Models

fastText supervised learning

A fastText classifier is built on top of a linear classifier, specifically a BoW classifier. In this section, you will get to know the architecture of the fastText classifier and how it works.


You can consider that each piece of text and each label is actually a vector in space and the coordinates of that vector are what we are actually trying to tweak and train so that the vector for a text and associated label are really close in space:

Vector representation of the text

So, in this example, which is an example shown in 2D space, you have texts that are saying things such as "Nigerian Tommy Thompson is also a relative newcomer to the wrestling scene" and "James...