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- Herausgeber: Packt Publishing
- Kategorie: Fachliteratur
- Sprache: Englisch
- Veröffentlichungsjahr: 2021
fastai is an easy-to-use deep learning framework built on top of PyTorch that lets you rapidly create complete deep learning solutions with as few as 10 lines of code. Both predominant low-level deep learning frameworks, TensorFlow and PyTorch, require a lot of code, even for straightforward applications. In contrast, fastai handles the messy details for you and lets you focus on applying deep learning to actually solve problems.
The book begins by summarizing the value of fastai and showing you how to create a simple 'hello world' deep learning application with fastai. You'll then learn how to use fastai for all four application areas that the framework explicitly supports: tabular data, text data (NLP), recommender systems, and vision data. As you advance, you'll work through a series of practical examples that illustrate how to create real-world applications of each type. Next, you'll learn how to deploy fastai models, including creating a simple web application that predicts what object is depicted in an image. The book wraps up with an overview of the advanced features of fastai.
By the end of this fastai book, you'll be able to create your own deep learning applications using fastai. You'll also have learned how to use fastai to prepare raw datasets, explore datasets, train deep learning models, and deploy trained models.
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Deep Learning with fastai Cookbook
Leverage the easy-to-use fastai framework to unlock the power of deep learning
Mark Ryan
BIRMINGHAM—MUMBAI
Deep Learning with fastai Cookbook
Copyright © 2021 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
Group Product Manager: Kunal Parikh
Publishing Product Manager: Ali Abidi
Senior Editor: Roshan Kumar
Content Development Editor: Tazeen Shaikh
Technical Editor: Sonam Pandey
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First published: August 2021
Production reference: 1210721
Published by Packt Publishing Ltd.
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ISBN 978-1-80020-810-0
www.packt.com
To the memory of my father, Ben. He would have loved fastai.– Mark Ryan
Contributors
About the author
Mark Ryan is a machine learning practitioner and technology manager who is passionate about delivering end-to-end deep learning applications that solve real-world problems. Mark has worked on deep learning projects that incorporate a variety of related technologies, including Rasa chatbots, web applications, and messenger platforms. As a strong believer in democratizing technology, Mark advocates for Keras and fastai as accessible frameworks that open up deep learning to non-specialists. Mark has a degree in computer science from the University of Waterloo and a Master of Science degree in computer science from the University of Toronto.
I want to thank my family for their support during the development of this book. In particular, I would like to acknowledge my nephew, Rowan Hansen, for his advice on web development. My friends, in particular Dr. Laurence Mussio, Peter Moroney, Luc Chamberland, and Alan Hall, provided much-appreciated support to me while I wrote this book. Finally, I would like to thank the team at Packt for guiding me through the process of completing this book.
About the reviewer
Rupsi Kaushik is a backend engineer at the Paris-based AI start-up reciTAL. She graduated from the University of Ottawa with a B.Sc. in computer science with an option in entrepreneurship and management. Her interest in machine learning was first sparked when she created her first search engine from scratch, and it has grown ever since. She hopes to learn more about AI for social good and make a meaningful impact on the world.
