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Paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Paperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
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Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD
Seller: Goodwill of Silicon Valley, SAN JOSE, CA, U.S.A.
Seller rating 4 out of 5 stars
Condition: good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Good condition! Any other included accessories are also in Good condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear.
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Deep Learning for Coders with
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
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Condition: very_good. Gently read. May have name of previous ownership, or ex-library edition. Binding tight; spine straight and smooth, with no creasing; covers clean and crisp. Minimal signs of handling or shelving. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item for full refund. Ships USPS Media Mail.
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US$ 22.79
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Add to basketCondition: like new. EXPEDITION SOUS 48 H EN SUIVI LA POSTE / EMBALLAGE BULLEPACK.
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paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!
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Add to basketSoftcover. Condition: Très bon. Ancien livre de bibliothèque avec équipements. Edition 2017. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 2017. Ammareal gives back up to 15% of this item's net price to charity organizations.
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Condition: New. Supporting Bay Area Friends of the Library since 2010. Well packaged and promptly shipped.
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Add to basketSoftcover. Condition: Bon. Ancien livre de bibliothèque avec équipements. Edition 2018. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Edition 2018. Ammareal gives back up to 15% of this item's net price to charity organizations.
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Add to basketSoftcover. Condition: Bon. Ancien livre de bibliothèque. Petite(s) trace(s) de pliure sur la couverture. Pages cornées. Notes en marge. Tampon ou marque sur la face intérieure de la couverture. Edition 2018. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisation ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Slightly creased cover. Dog-eared pages. Notes on page margins. Stamp or mark on the inside cover page. Edition 2018. Ammareal gives back up to 15% of this item's net price to charity organizations.
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paperback. Condition: New.
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US$ 11.99
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Add to basketSoftcover. Condition: Bon. Ancien livre de bibliothèque avec équipements. Edition 2018. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Edition 2018. Ammareal gives back up to 15% of this item's net price to charity organizations.
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![Stock image for Maths - Exercices incontournables - PC-PSI - 4e éd. [Broché] Bernard, Pierre; Mansuy, Mathieu; Chalmin, Anne-Charline; Devys, Oscar; Virat, Marie; Freslon, Julien; Gugger, Sylvain; Fredon, Daniel et Poineau, Jérôme for sale by BIBLIO-NET](https://pictures.abebooks.com/isbn/9782100864713-us-300.jpg)
US$ 33.59
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![Stock image for Maths PC/PC* [Broché] Gugger, Sylvain; Lemberg, Henri; Rozsavolgyi, Gérard et Pater, Laurent for sale by BIBLIO-NET](https://pictures.abebooks.com/isbn/9782100841721-us-300.jpg)
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Condition: New.
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Paperback. Condition: New. Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.Train models in computer vision, natural language processing, tabular data, and collaborative filteringLearn the latest deep learning techniques that matter most in practiceImprove accuracy, speed, and reliability by understanding how deep learning models workDiscover how to turn your models into web applicationsImplement deep learning algorithms from scratchConsider the ethical implications of your workGain insight from the foreword by PyTorch cofounder, Soumith Chintala.
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Deep Learning for Coders with fastai and PyTorch (Paperback)
Published by O'Reilly Media, Sebastopol, 2020
ISBN 10: 1492045527 ISBN 13: 9781492045526
Language: English
Paperback. Condition: new. Paperback. Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.Train models in computer vision, natural language processing, tabular data, and collaborative filteringLearn the latest deep learning techniques that matter most in practiceImprove accuracy, speed, and reliability by understanding how deep learning models workDiscover how to turn your models into web applicationsImplement deep learning algorithms from scratchConsider the ethical implications of your workGain insight from the foreword by PyTorch cofounder, Soumith Chintala Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Deep Learning for Coders With Fastai and Pytorch : AI Applications Without a Phd
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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US$ 56.53
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Deep Learning for Coders With Fastai and Pytorch : AI Applications Without a Phd
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 58.92
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Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 66.53
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Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD
Published by O'Reilly Media, Inc. 2020-08-21, 2020
ISBN 10: 1492045527 ISBN 13: 9781492045526
Language: English
US$ 65.15
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Deep Learning for Coders with fastai and PyTorch
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
US$ 85.58
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Add to basketPaperback. Condition: New. Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.Train models in computer vision, natural language processing, tabular data, and collaborative filteringLearn the latest deep learning techniques that matter most in practiceImprove accuracy, speed, and reliability by understanding how deep learning models workDiscover how to turn your models into web applicationsImplement deep learning algorithms from scratchConsider the ethical implications of your workGain insight from the foreword by PyTorch cofounder, Soumith Chintala.
