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fastText Quick Start Guide

You're reading from fastText Quick Start Guide Get started with Facebook's library for text representation and classification

Product type Paperback

Published in Jul 2018

Publisher Packt

ISBN-13 9781789130997

Length 194 pages

Edition 1st Edition

Languages

Python

Tools

fastText

Concepts

Mobile Application Development

Author (1):

Joydeep Bhattacharjee

View More author details

Table of Contents (14) Chapters

Preface

1. First Steps

2. Introducing FastText FREE CHAPTER

3. Creating Models Using FastText Command Line

4. The FastText Model

5. Word Representations in FastText

6. Sentence Classification in FastText

7. Using FastText in Your Own Models

8. FastText in Python

9. Machine Learning and Deep Learning Models

10. Deploying Models to Web and Mobile

11. Notes for the Readers

12. References

13. Other Books You May Enjoy

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Chapter 4

Vladimir Zolotov and David Kung 2017, Analysis and Optimization of fastText Linear Text Classifier, http://arxiv.org/abs/1702.05531
Text classification of linear models, http://www.cs.umd.edu/class/fall2017/cmsc723/slides/slides_03.pdf
What is text classification, Stanford, https://nlp.stanford.edu/IR-book/html/htmledition/the-text-classification-problem-1.html#sec:classificationproblem
https://nlp.stanford.edu/IR-book/html/htmledition/text-classification-and-naive-bayes-1.html
https://research.fb.com/fasttext/
Bag of tricks for efficient classification, arXiv:1607.01759v3 [cs.CL] 9 Aug 2016
https://github.com/poliglot/fasttext
Joseph Turian, Lev Ratinov, and Yoshua Bengio, 2010, Word representations: A simple and general method for semi-supervised learning, In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL '10), Association...

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Authors (1)

Joydeep Bhattacharjee

Joydeep Bhattacharjee

Joydeep Bhattacharjee is a Principal Engineer who works for Nineleaps Technology Solutions. After graduating from National Institute of Technology at Silchar, he started working in the software industry, where he stumbled upon Python. Through Python, he stumbled upon machine learning. Now he primarily develops intelligent systems that can parse and process data to solve challenging problems at work. He believes in sharing knowledge and loves mentoring in machine learning. He also maintains a machine learning blog on Medium.

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