Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

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

Leave a review - let other readers know what you think

Summary

In this chapter, we took a look at the methodologies to implement fastText in a web and mobile context, focusing specifically on Android. We also took a look at the different considerations that you need to bear in mind, depending on whether you need to deploy on web or mobile. This should help you to create good applications and integrate fastText into your mobile applications.

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $19.99/month. Cancel anytime

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.

See other products by Joydeep Bhattacharjee

Other recommended products

Related to this chapter

Hands-On Python Natural Language Processing

Hands-On Python Natural Language Processing

This book provides a blend of both the theoretical and practical aspects of Natural Language Processing (NLP). It covers the concepts essential to develop a thorough understanding of NLP and also delves into a detailed discussion on NLP based use-cases such as language translation, sentiment analysis, etc. Every module covers real-world examples

Jun 2020 10h 32m

Natural Language Processing and Computational Linguistics

Natural Language Processing and Computational Linguistics

Discover how you can perform your own modern text analysis, to make predictions, create inferences, and gain insights about the data around you today. Learn how to harness the powerful Python ecosystem and tools such as spaCy and Gensim to perform natural language processing, and computational linguistics algorithms.

Jun 2018 10h 12m

Natural Language Processing with Python Quick Start Guide

Natural Language Processing with Python Quick Start Guide

NLP in Python is among the most sought-after skills among data scientists. With code and relevant case studies, this book will show how you can use industry grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP.

Hands-On Natural Language Processing with Python

Hands-On Natural Language Processing with Python

This book teaches you to leverage deep learning models in performing various NLP tasks along with showcasing the best practices in dealing with the NLP challenges. The book equips you with practical knowledge to implement deep learning in your linguistic applications using NLTk and Python's popular deep learning library, TensorFlow.

Jul 2018 10h 24m

Mastering spaCy

Mastering spaCy

Using machine learning-based NLP models, you can speed up business processes, make more accurate predictions, and uncover new insights from your existing data, where spaCy, an advanced industrial-grade natural language processing library, can help. With this book, you'll learn how to use it and create high-impact ML solutions for NLP.

Jul 2021 11h 52m

Natural Language Processing with TensorFlow

Natural Language Processing with TensorFlow

TensorFlow is the leading framework for deep learning algorithms critical to artificial intelligence, and natural language processing (NLP) makes much of the data used by deep learning applications accessible to them. This book brings the two together and teaches deep learning developers how to work with today's vast amount of unstructured data.

May 2018 15h 44m

Hands-On Natural Language Processing with PyTorch 1.x

Hands-On Natural Language Processing with PyTorch 1.x

Developers working with NLP will be able to put their knowledge to work with this practical guide to PyTorch. You will learn to use PyTorch offerings and how to understand and analyze text using Python. You will learn to extract the underlying meaning in the text using deep neural networks and modern deep learning algorithms.

Jul 2020 9h 12m

Deep Learning Essentials

Deep Learning Essentials

Deep Learning is one of the trending topics in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning. This book will help you take your first steps when it comes to training efficient deep learning models, and apply them in various practical scenarios. You will model, train and deploy different kinds of neural networks such as Convolutional Neural Network, Recurrent Neural Network, and see their applications in real-world domains such as computer vision, natural language processing, and speech recognition. This book also covers solutions to tackle different problems you might come across while training your models and ensure their high performance. This book does not assume any prior knowledge of deep learning. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications.

Jan 2018 9h 28m

Mastering Transformers

Mastering Transformers

Explore the accurate and fast fine-tuning capabilities of transformer-based language models and understand how they outperform traditional machine learning-based approaches when solving challenging NLU problems. Developers working with the Transformers architecture will be able to put their knowledge to work with this practical guide.

Sep 2021 12h 28m

Python Natural Language Processing

Python Natural Language Processing

Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. The numbers of human-computer interaction instances are increasing so it's becoming imperative that computers comprehend all major natural languages. Python's powerful tools and libraries are evolved so much that natural language processing becomes much simpler and accurate with it. This book will get you up and running with Python's library for Natural Language Processing-- NLTK-- in no time.

Jul 2017 16h 12m

TensorFlow Machine Learning Projects

TensorFlow Machine Learning Projects

This book will show you how to take advantage of TensorFlow's most appealing features - simplicity, efficiency, and flexibility - in various scenarios. You will gain cutting-edge insights into using TensorFlow's offerings for your problems and learn practical hacks to successfully implement real-world machine learning projects.

Nov 2018 10h 44m

Deep Learning with TensorFlow 2 and Keras

Deep Learning with TensorFlow 2 and Keras

Deep Learning with TensorFlow 2 and Keras, Second Edition teaches deep learning techniques alongside TensorFlow (TF) and Keras. The book introduces neural networks with TensorFlow, runs through the main applications, covers two working example apps, and then dives into TF and cloudin production, TF mobile, and using TensorFlow with AutoML.

Dec 2019 21h 32m