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

Machine Learning and Deep Learning Models

In almost all of the applications that we have been discussing up to now, the implicit assumption has been that you are creating a new machine learning NLP pipeline. Now, that may not always be the case. If you are already working on an established platform, fastText may also be a good addition to make the pipeline better.

This chapter will give you some of the methods and recipes for implementing fastText using popular frameworks such as scikit-learn, Keras, TensorFlow, and PyTorch. We will look at how we can augment the power of word embeddings in fastText, using other deep neural architectures such as convolutional neural networks (CNN) or attention networks to solve various NLP problems.

The topics covered in this chapter are as follows:

  • Scikit-learn and fastText
  • Embeddings
  • Keras
  • Embeddings layer in Keras
  • Convolutional neural network...