Shruti Jadon - Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch
Here you can read online Shruti Jadon - Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch full text of the book (entire story) in english for free. Download pdf and epub, get meaning, cover and reviews about this ebook. year: 2020, publisher: Packt Publishing, genre: Children. Description of the work, (preface) as well as reviews are available. Best literature library LitArk.com created for fans of good reading and offers a wide selection of genres:
Romance novel
Science fiction
Adventure
Detective
Science
History
Home and family
Prose
Art
Politics
Computer
Non-fiction
Religion
Business
Children
Humor
Choose a favorite category and find really read worthwhile books. Enjoy immersion in the world of imagination, feel the emotions of the characters or learn something new for yourself, make an fascinating discovery.
- Book:Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch
- Author:
- Publisher:Packt Publishing
- Genre:
- Year:2020
- Rating:5 / 5
- Favourites:Add to favourites
- Your mark:
Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch: summary, description and annotation
We offer to read an annotation, description, summary or preface (depends on what the author of the book "Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch" wrote himself). If you haven't found the necessary information about the book — write in the comments, we will try to find it.
Get to grips with building powerful deep learning models using PyTorch and scikit-learn
Key Features- Learn how you can speed up the deep learning process with one-shot learning
- Use Python and PyTorch to build state-of-the-art one-shot learning models
- Explore architectures such as Siamese networks, memory-augmented neural networks, model-agnostic meta-learning, and discriminative k-shot learning
One-shot learning has been an active field of research for scientists trying to develop a cognitive machine that mimics human learning. With this book, youll explore key approaches to one-shot learning, such as metrics-based, model-based, and optimization-based techniques, all with the help of practical examples.
Hands-On One-shot Learning with Python will guide you through the exploration and design of deep learning models that can obtain information about an object from one or just a few training samples. The book begins with an overview of deep learning and one-shot learning and then introduces you to the different methods you can use to achieve it, such as deep learning architectures and probabilistic models. Once youve got to grips with the core principles, youll explore real-world examples and implementations of one-shot learning using PyTorch 1.x on datasets such as Omniglot and MiniImageNet. Finally, youll explore generative modeling-based methods and discover the key considerations for building systems that exhibit human-level intelligence.
By the end of this book, youll be well-versed with the different one- and few-shot learning methods and be able to use them to build your own deep learning models.
What you will learn- Get to grips with the fundamental concepts of one- and few-shot learning
- Work with different deep learning architectures for one-shot learning
- Understand when to use one-shot and transfer learning, respectively
- Study the Bayesian network approach for one-shot learning
- Implement one-shot learning approaches based on metrics, models, and optimization in PyTorch
- Discover different optimization algorithms that help to improve accuracy even with smaller volumes of data
- Explore various one-shot learning architectures based on classification and regression
If youre an AI researcher or a machine learning or deep learning expert looking to explore one-shot learning, this book is for you. It will help you get started with implementing various one-shot techniques to train models faster. Some Python programming experience is necessary to understand the concepts covered in this book.
Table of Contents- Introduction to One-shot Learning
- Metrics-Based Methods
- Models-Based Methods
- Optimization-Based Methods
- Generative Modeling-Based Methods
- Conclusion and Other Approaches
Shruti Jadon: author's other books
Who wrote Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch? Find out the surname, the name of the author of the book and a list of all author's works by series.
Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch — read online for free the complete book (whole text) full work
Below is the text of the book, divided by pages. System saving the place of the last page read, allows you to conveniently read the book "Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch" online for free, without having to search again every time where you left off. Put a bookmark, and you can go to the page where you finished reading at any time.
Font size:
Interval:
Bookmark:
Copyright 2019 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 authors, 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.
Commissioning Editor: Amey Varangaonkar
Acquisition Editor: Yogesh Deokar
Content Development Editor: Athikho Sapuni Rishana
Senior Editor: Sofi Rogers
Technical Editor: Manikandan Kurup
Copy Editor: Safis Editing
Project Coordinator: Aishwarya Mohan
Proofreader: Safis Editing
Indexer: Priyanka Dhadke
Production Designer: Jyoti Chauhan
First published: April 2020
Production reference: 1090420
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham
B3 2PB, UK.
ISBN 978-1-83882-546-1
www.packtpub.com
Packt.com
Subscribe to our online digital library for full access to over 7,000 books and videos, as well as industry leading tools to help you plan your personal development and advance your career. For more information, please visit our website.
Spend less time learning and more time coding with practical eBooks and Videos from over 4,000 industry professionals
Improve your learning with Skill Plans built especially for you
Get a free eBook or video every month
Fully searchable for easy access to vital information
Copy and paste, print, and bookmark content
Did you know that Packt offers eBook versions of every book published, with PDF and ePub files available? You can upgrade to the eBook version at www.packt.com and as a print book customer, you are entitled to a discount on the eBook copy. Get in touch with us at customercare@packtpub.com for more details.
At www.packt.com , you can also read a collection of free technical articles, sign up for a range of free newsletters, and receive exclusive discounts and offers on Packt books and eBooks.
Shruti Jadon is currently working as a Machine Learning Software Engineer at Juniper Networks, Sunnyvale and visiting Researcher at Rhode Island Hospital (Brown University). She has obtained her master's degree in Computer Science from University of Massachusetts, Amherst. Her research interests include deep learning architectures, computer vision, and convex optimization. In the past, she has worked at Autodesk, Quantiphi, SAP Labs, and Snapdeal.
Ankush Garg is currently working as a Software Engineer in the auto-translation team at Google, Mountain View. He has obtained his master's degree in Computer Science from the University of Massachusetts, Amherst, and his bachelor's at NSIT, Delhi. His research interests include language modeling, model compression, and optimization. In the past, he has worked as a Software Engineer at Amazon, India.
Greg Walters has been involved with computers and computer programming since 1972. He is well versed in Visual Basic, Visual Basic.NET, Python, and SQL, and is an accomplished user of MySQL, SQLite, Microsoft SQL Server, Oracle, C++, Delphi, Modula-2, Pascal, C, 80x86 Assembler, COBOL, and Fortran. He is a programming trainer and has trained numerous individuals in many pieces of computer software, including MySQL, Open Database Connectivity, Quattro Pro, Corel Draw!, Paradox, Microsoft Word, Excel, DOS, Windows 3.11, Windows for Workgroups, Windows 95, Windows NT, Windows 2000, Windows XP, and Linux. He is currently retired and, in his spare time, is a musician and loves to cook. He is also open to working as a freelancer on various projects.
If you're interested in becoming an author for Packt, please visit authors.packtpub.com and apply today. We have worked with thousands of developers and tech professionals, just like you, to help them share their insight with the global tech community. You can make a general application, apply for a specific hot topic that we are recruiting an author for, or submit your own idea.
One-shot learning has been an active field of research for many scientists who are trying to find a cognitive machine that is as close to human beings as possible in terms of learning. As there are various theories as to how humans effect one-shot learning, there are a variety of different methods available to achieve this, ranging from non-parametric models and deep learning architectures to probabilistic models.
Hands-On One-shot Learning with Python will focus on designing and learning about models that can learn information relating to an object from one, or only a few, training examples. The book will begin by giving you a brief overview of deep learning and one-shot learning to get you started. Then, you will learn different methods to achieve this, including non-parametric models, deep learning architectures, and probabilistic models. Once you are well versed in the core principles, you will explore some of the practical real-world examples and implementations of one-shot learning using scikit-learn and PyTorch.
By the end of the book, you will be familiar with one-shot and few-shots learning methods and be able to accelerate your deep learning processes with one-shot learning.
AI researchers, as well as machine learning and deep learning experts who wish to apply one-shot learning to reduce the overall training time of their models, will find this book to be a very good introductory source of learning.
, Introduction to One-shot Learning , tells us what one-shot learning is and how it works. It also tells us about the human brain's workings and how it translates to machine learning.
, Metrics-Based Methods , explores methods that use different forms of embeddings, and evaluation metrics, by keeping the core as basic k-nearest neighbors.
Next pageFont size:
Interval:
Bookmark:
Similar books «Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch»
Look at similar books to Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch. We have selected literature similar in name and meaning in the hope of providing readers with more options to find new, interesting, not yet read works.
Discussion, reviews of the book Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch and just readers' own opinions. Leave your comments, write what you think about the work, its meaning or the main characters. Specify what exactly you liked and what you didn't like, and why you think so.