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

Using a Docker image for fastText

You can also use Docker to run fastText on your machine and not worry about building it. This can be done to maintain version control between specific versions and thus gives us predictability and consistency. You can get information on how to install Docker from the following link: https://docs.docker.com/install/#cloud.

After installing, start the Docker service before running the following commands:

 start the docker service.
$ systemctl start docker

# run the below commands to start the fasttext container.
$ docker pull xebxeb/fasttext-docker

You should now be able to run fastText:

$ mkdir -p /tmp/data && mkdir -p /tmp/result
$ docker run --rm -v /tmp/data:/data -v /tmp/result:/result \
-it xebxeb/fasttext-docker ./classification-example.sh

You may need to provide permissions and create the specific directories to run the...