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fastText Quick Start Guide
fastText Quick Start Guide

fastText Quick Start Guide: Get started with Facebook's library for text representation and classification

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Profile Icon Joydeep Bhattacharjee
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€24.99
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.7 (3 Ratings)
Paperback Jul 2018 194 pages 1st Edition
eBook
€19.99
Paperback
€24.99
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Arrow left icon
Profile Icon Joydeep Bhattacharjee
Arrow right icon
€24.99
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.7 (3 Ratings)
Paperback Jul 2018 194 pages 1st Edition
eBook
€19.99
Paperback
€24.99
Subscription
Free Trial
Renews at €18.99p/m
eBook
€19.99
Paperback
€24.99
Subscription
Free Trial
Renews at €18.99p/m

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fastText Quick Start Guide

First Steps

On completion of this section, the reader will have working knowledge of how to install fastText and run the command line application effectively on any dataset.

In the Chapter 1, Introducing fastText, you will get a description of fastText and the Natural Language Processing (NLP) context in which this library is useful. It will map the motivations behind building the library, its intended use, and the benefits that the creators of the library wanted to bring to NLP and the field of Computational Linguistics. Furthermore, there will be specific instructions on how to install fastText on the reader's work machine. On completion of this chapter, the reader will have fastText installed and running on their computer.

In the Chapter 2, Creating Models Using the FastText Command Line, you will get to know about the rich command line that the fastText library provides. This chapter will give you descriptions of the default command line options and how to use them to create models. If the reader only has a superficial interest in fastText, reading till this chapter should be enough.

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Key benefits

  • Introduction to Facebook's fastText library for NLP
  • Perform efficient word representations, sentence classification, vector representation
  • Build better, more scalable solutions for text representation and classification

Description

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.

Who is this book for?

This book is for data analysts, data scientists, and machine learning developers who want to perform efficient word representation and sentence classification using Facebook's fastText library. Basic knowledge of Python programming is required.

What you will learn

  • Create models using the default command line options in fastText
  • Understand the algorithms used in fastText to create word vectors
  • Combine command line text transformation capabilities and the fastText library to implement a training, validation, and prediction pipeline
  • Explore word representation and sentence classification using fastText
  • Use Gensim and spaCy to load the vectors, transform, lemmatize, and perform other NLP tasks efficiently
  • Develop a fastText NLP classifier using popular frameworks, such as Keras, Tensorflow, and PyTorch
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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 26, 2018
Length: 194 pages
Edition : 1st
Language : English
ISBN-13 : 9781789130997
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Estimated delivery fee Deliver to Denmark

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Product Details

Publication date : Jul 26, 2018
Length: 194 pages
Edition : 1st
Language : English
ISBN-13 : 9781789130997
Vendor :
Facebook
Category :
Languages :
Tools :

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Table of Contents

13 Chapters
First Steps Chevron down icon Chevron up icon
Introducing FastText Chevron down icon Chevron up icon
Creating Models Using FastText Command Line Chevron down icon Chevron up icon
The FastText Model Chevron down icon Chevron up icon
Word Representations in FastText Chevron down icon Chevron up icon
Sentence Classification in FastText Chevron down icon Chevron up icon
Using FastText in Your Own Models Chevron down icon Chevron up icon
FastText in Python Chevron down icon Chevron up icon
Machine Learning and Deep Learning Models Chevron down icon Chevron up icon
Deploying Models to Web and Mobile Chevron down icon Chevron up icon
Notes for the Readers Chevron down icon Chevron up icon
References Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.7
(3 Ratings)
5 star 66.7%
4 star 0%
3 star 0%
2 star 0%
1 star 33.3%
Laxmi Vanam Sep 24, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Having followed Joydeep's lectures (youtube channel and seminars) for a while, I got this book hoping to get an indepth understanding of the fasttext library while working on my NLP project. I would say, it absolutely met my expectations in taking me from zero-in-depth understanding of the concepts. I have always believed that books are deeper way to dive into the subject compared to online lectures and this book proved to be right. I can say with just the super basic knowledge of what NLP is you can rely on this book to take you to a next level. All the concepts are explained in a lucid manner and can me sense to an absolute beginner in NLP. I would recommend this book to anyone who wants to get absolute understanding of fastText library for text classification on both supervised and unsupervised representations.
Amazon Verified review Amazon
MJ Oct 23, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I've been using fastText for about 6 months now. I had not been able to find any good resources that simply explained all of the necessary steps to prepare text training data before building a FastText model. It was also very hard to know how to tweak the supervised hyperparameters. This books answered my questions!I'm so thankful for Joydeep Bhattacharjee and his hard work on this fantastic resource.
Amazon Verified review Amazon
C. Vogel May 10, 2020
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Bash scripts, really?By today standards, one would expect a clean support of notebooks or organized code per chapter. Not a mixed bag of 5 lines Python functions, and command line scripts.
Amazon Verified review Amazon
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