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 official bindings

The steps to install the official bindings for Python are covered in the first chapter. In this section, we will cover how to use the official fastText Python package to train, load, and use the models.

Using the Python fastText library, you will be able to implement all the necessary features that can be done using the command line. Lets take a look at the ways to implement unsupervised and supervised learning using Python fastText.

Note: In this chapter, we will be using Python3 and so the code examples will be in that. For users who are using Python2, please take a look at the Appendix for notes on the considerations that you need to bear in mind when using Python2.


Python bindings for...