Deep Learning with PyTorch Lightning : Swiftly build high-performance Artificial Intelligence (AI) models using Python
Language: English
Published by Packt Publishing, 2022
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 73.31
Quantity: 1 available
Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - Build, train, deploy, and scale deep learning models quickly and accurately, improving your productivity using the lightweight PyTorch WrapperKey Features:Become well-versed with PyTorch Lightning architecture and learn how it can be implemented in various industry domainsSpeed up your research using PyTorch Lightning by creating new loss functions, networks, and architecturesTrain and build new algorithms for massive data using distributed trainingBook Description:PyTorch Lightning lets researchers build their own Deep Learning (DL) models without having to worry about the boilerplate. With the help of this book, you'll be able to maximize productivity for DL projects while ensuring full flexibility from model formulation through to implementation. You'll take a hands-on approach to implementing PyTorch Lightning models to get up to speed in no time.You'll start by learning how to configure PyTorch Lightning on a cloud platform, understand the architectural components, and explore how they are configured to build various industry solutions. Next, you'll build a network and application from scratch and see how you can expand it based on your specific needs, beyond what the framework can provide. The book also demonstrates how to implement out-of-box capabilities to build and train Self-Supervised Learning, semi-supervised learning, and time series models using PyTorch Lightning. As you advance, you'll discover how generative adversarial networks (GANs) work. Finally, you'll work with deployment-ready applications, focusing on faster performance and scaling, model scoring on massive volumes of data, and model debugging.By the end of this PyTorch book, you'll have developed the knowledge and skills necessary to build and deploy your own scalable DL applications using PyTorch Lightning.What You Will Learn:Customize models that are built for different datasets, model architectures, and optimizersUnderstand how a variety of Deep Learning models from image recognition and time series to GANs, semi-supervised and self-supervised models can be builtUse out-of-the-box model architectures and pre-trained models using transfer learningRun and tune DL models in a multi-GPU environment using mixed-mode precisionsExplore techniques for model scoring on massive workloadsDiscover troubleshooting techniques while debugging DL modelsWho this book is for:This deep learning book is for citizen data scientists and expert data scientists transitioning from other frameworks to PyTorch Lightning. This book will also be useful for deep learning researchers who are just getting started with coding for deep learning models using PyTorch Lightning. Working knowledge of Python programming and an intermediate-level understanding of statistics and deep learning fundamentals is expected.…
Seller Inventory # 9781800561618
- Title
- Deep Learning with PyTorch Lightning : Swiftly build high-performance Artificial Intelligence (AI) models using Python
- Author
- Kunal Sawarkar
- Publisher
- Packt Publishing
- Publication year
- 2022
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 180056161X
- ISBN 13
- 9781800561618
- Item weight
- 683 grams
- Dimensions
- 235x191x20 mm
Build, train, deploy, and scale deep learning models quickly and accurately, improving your productivity using the lightweight PyTorch Wrapper
Key Features
- Become well-versed with PyTorch Lightning architecture and learn how it can be implemented in various industry domains
- Speed up your research using PyTorch Lightning by creating new loss functions, networks, and architectures
- Train and build new algorithms for massive data using distributed training
Book Description
PyTorch Lightning lets researchers build their own Deep Learning (DL) models without having to worry about the boilerplate. With the help of this book, you'll be able to maximize productivity for DL projects while ensuring full flexibility from model formulation through to implementation. You'll take a hands-on approach to implementing PyTorch Lightning models to get up to speed in no time.
You'll start by learning how to configure PyTorch Lightning on a cloud platform, understand the architectural components, and explore how they are configured to build various industry solutions. Next, you'll build a network and application from scratch and see how you can expand it based on your specific needs, beyond what the framework can provide. The book also demonstrates how to implement out-of-box capabilities to build and train Self-Supervised Learning, semi-supervised learning, and time series models using PyTorch Lightning. As you advance, you'll discover how generative adversarial networks (GANs) work. Finally, you'll work with deployment-ready applications, focusing on faster performance and scaling, model scoring on massive volumes of data, and model debugging.
By the end of this PyTorch book, you'll have developed the knowledge and skills necessary to build and deploy your own scalable DL applications using PyTorch Lightning.
What you will learn
- Customize models that are built for different datasets, model architectures, and optimizers
- Understand how a variety of Deep Learning models from image recognition and time series to GANs, semi-supervised and self-supervised models can be built
- Use out-of-the-box model architectures and pre-trained models using transfer learning
- Run and tune DL models in a multi-GPU environment using mixed-mode precisions
- Explore techniques for model scoring on massive workloads
- Discover troubleshooting techniques while debugging DL models
Who this book is for
This deep learning book is for citizen data scientists and expert data scientists transitioning from other frameworks to PyTorch Lightning. This book will also be useful for deep learning researchers who are just getting started with coding for deep learning models using PyTorch Lightning. Working knowledge of Python programming and an intermediate-level understanding of statistics and deep learning fundamentals is expected.
Table of Contents
- PyTorch Lightning Adventure
- Getting Off the Ground with Your First Deep Learning Model
- Transfer Learning Using Pre-Trained Models
- Ready-to- Use Models from Bolts
- Time Series Models
- Deep Generative Models
- Semi-Supervised Learning
- Self-Supervised Learning
- Deploying and Scoring Models
- Scaling and Managing Training
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
Shipping rates from Germany to U.S.A.
| Item | 5 to 7 business days | 7 to 10 business days |
|---|---|---|
| First item | £ 26.15 | £ 26.15 |
Payment methods
- Bank Wire Transfer
- Check
- Paypal
Store description
Das Unternehmen AHA-BUCH GmbH: Seit der Gründung von AHA-BUCH im Juli 2005 ist unser Hauptziel, zufriedenen Kunden so schnell und so preisgünstig wie möglich ihren Bücherwunsch zu erfüllen. Unsere Firma beschäftigt 16 Mitarbeiter, die nur ein Ziel kennen: den Kunden und seine Wünsche! Auf über 3700 m2 Fläche haben wir über 100.000 Bücher, Modernes Antiquariat und Spiele auf Lager.
Specialty
Kinderbücher & Kinderhör Casetten, German Books, Software, Natur & Tiere, Ratgeber, Sachbücher, Englische Bücher, Medizin & Gesundheit, Universität & StudiumSeller's business information
AHA-BUCH GmbH
Garlebsen 48
Einbeck, Germany 37574
Terms of sale
Imprint
Seller Info:
AHA-BUCH GmbH
represented by the managing director Christel Glass
Garlebsen 48
37574 Einbeck
Deutschland
Telefon: 055639996039
Telefax: 055639995974
E-Mail: abebooks@aha-buch.de
USt-IdNr.: DE261904229
registered at Commercial register Amtsgerichtes Göttingen
Handelsregisternummer HRB 200691
Alternative dispute resolution:
The European Commission provides a platform for out-of-court online dispute resolution (ODR platform), which can be accessed under https://ec.europa.eu/odr.
We have been a member of the "FairCommerce" initiative since 25.05.2018.
For more information, see www.fair-commerce.de.
Right of withdrawal
If you are a consumer you can withdraw from the contract in accordance with the following. Consumer means any natural person who is acting for purposes which are outside his trade, business, craft or profession.
Information regarding the right of withdrawal
Statutory right to withdraw
You have the right to withdraw from this contract within 14 days without giving any reason.
The withdrawal period will expire after 14 days from the day on which you acquire, or a third party other than the carrier and indicated by you acquires, physical possession of the last good or the last lot or piece.
To exercise the right of withdrawal, electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". We will communicate to you an acknowledgement of receipt of such a withdrawal on a durable medium (e.g. by e-mail) without delay.
To meet the withdrawal deadline, it is sufficient for you to send your communication concerning your exercise of the right of withdrawal before the withdrawal period has expired.
Effects of withdrawal
If you withdraw from this contract, we will reimburse to you all payments received from you, including the costs of delivery (except for the supplementary costs arising if you chose a type of delivery other than the least expensive type of standard delivery offered by us).
We may make a deduction from the reimbursement for loss in value of any goods supplied, if the loss is the result of unnecessary handling by you.
We will make the reimbursement without undue delay, and not later than 14 days after the day on which we are informed about your decision to withdraw from this contract.
We will make the reimbursement using the same means of payment as you used for the initial transaction, unless you have expressly agreed otherwise; in any event, you will not incur any fees as a result of such reimbursement.
We may withhold reimbursement until we have received the goods back, or you have supplied evidence of having sent back the goods, whichever is the earliest.
You shall send back the goods or hand them over to AHA-BUCH GmbH, Einbeck, Germany, without undue delay and in any event not later than 14 days from the day on which you communicate your withdrawal from this contract to us. The deadline is met if you send back the goods before the period of 14 days has expired. You will have to bear the direct cost of returning the goods. You are only liable for any diminished value of the goods resulting from the handling other than what is necessary to establish the nature, characteristics and functioning of the goods.
Exceptions to the right of withdrawal
The right of withdrawal does not apply to:
- The delivery of newspapers, journals or magazines with the exception of subscription contracts; and
- The supply of digital content which is not supplied on a tangible medium (e.g. on a CD or DVD) if you accepted when you placed your order that we could start to deliver it, and that you could not withdraw once delivery had started.
Shipping terms
We ship your order after we received them
for articles on hand latest 24 hours,
for articles with overnight supply latest 48 hours.
In case we need to order an article from our supplier our dispatch time depends on the reception date of the articles, but the articles will be shipped on the same day.
Our goal is to send the ordered articles in the fastest, but also most efficient and secure way to our customers.