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Deep Learning for Coders with
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Seller rating 5 out of 5 stars
Condition: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.
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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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Softcover. 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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Softcover. 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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Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD
Seller: WorldofBooks, Goring-By-Sea, WS, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
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Condition: like new. EXPEDITION SOUS 48 H EN SUIVI LA POSTE / EMBALLAGE BULLEPACK.
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Condition: New. SUPER FAST SHIPPING.
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Condition: as new. Appears unread. May have a retail sticker on back cover or remainder mark on the text block.
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Condition: As New. Unread book in perfect condition.
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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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![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-uk-300.jpg)
Condition: like new. EXPEDITION SOUS 48 H EN SUIVI LA POSTE / EMBALLAGE BULLEPACK / Impact sur tranche / Sinon impeccable.
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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
Condition: New.
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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
Condition: As New. Unread book in perfect condition.
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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
Condition: New. In.
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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
Paperback. Condition: New.
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Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD
Published by O'Reilly Media, Inc., 2020
ISBN 10: 1492045527 ISBN 13: 9781492045526
Language: English
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New. 2020. Paperback. . . . . .
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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-uk-300.jpg)
Condition: like new. EXPEDITION SOUS 48 H EN SUIVI LA POSTE / EMBALLAGE BULLEPACK.
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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
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: AI Applications Without a PhD
Published by O'Reilly Media, Inc, USA, 2020
ISBN 10: 1492045527 ISBN 13: 9781492045526
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD
Published by O'Reilly Media, Inc., 2020
ISBN 10: 1492045527 ISBN 13: 9781492045526
Language: English
Condition: New. 2020. Paperback. . . . . . Books ship from the US and Ireland.
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Condition: fine. couverture souple, moyen format , très bon état. . 3174927 - Maths PSI, Gugger, Sylvain, Dunod, 2017.
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Condition: fine. couverture souple, moyen format , très bon état. Couverture cornée. 3174860 - Maths PSI, Gugger, Sylvain, Dunod, 2017.
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Condition: New. pp. 350.
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Deep Learning for Coders With Fastai and Pytorch: Ai Applications Without a Phd
Published by Oreilly & Associates Inc, 2020
ISBN 10: 1492045527 ISBN 13: 9781492045526
Language: English
Paperback. Condition: Brand New. 350 pages. 9.25x7.25x1.00 inches. In Stock.
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Condition: New. pp. 350.
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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.
