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

Word Representations in FastText

Now that you have taken a look at creating models in the command line, you might be wondering how fastText creates those word representations. In this chapter, you will get to know what happens behind the scenes and the algorithms that power fastText.

We will cover the following topics in this chapter:

  • Word-to-vector representations
  • Types of word representations
  • Getting vector representations from text
  • Model architecture in fastText
  • The unsupervised model
  • fastText skipgram implementation
  • CBOW (Continuous bag of words)
  • Comparison between skipgram and CBOW
  • Loss functions and optimizations
  • Softmax
  • Context definitions