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
1
First Steps
4
The FastText Model
7
Using FastText in Your Own Models

Scikit-learn and fastText

In this section, we will be talking about how to integrate fastText into your statistical models. The most common and popular library for statistical machine learning is scikit-learn, so we will focus on that.

scikit-learn is one of the most popular machine learning tools and the reason is that the API is very simple and uniform. The flow is like this:

  1. You basically convert your data into matrix format.
  2. Then, you create an instance of the predictor class.
  3. Using the instance, you run the fit method on the data.
  4. Once the model is created, you can run predict on it.

This means that you can create a custom classifier by defining the fit and predict methods.

Custom classifiers for fastText

Since we...