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Deep Learning Coders Fastai by Jeremy Howard (31 results)
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paperback. Condition: Very Good. Orders shipped daily from the UK. Professional seller.
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paperback. Condition: Used; Very Good. Dispatched, from the UK, within 48 hours of ordering. Though second-hand, the book is still in very good shape. Minimal signs of usage may include very minor creasing on the cover or on the spine.
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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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Deep Learning for Coders with fastai and PyTorch
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Deep Learning for Coders With Fastai and Pytorch : AI Applications Without a Phd
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Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD
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Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD (Paperback or Softback)
Published by O'Reilly Media 8/4/2020, 2020
ISBN 10: 1492045527 ISBN 13: 9781492045526
Language: English
£ 43.15
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Add to basketPaperback or Softback. Condition: New. Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD 2.05. Book.
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£ 54.50
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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.
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Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD
Seller: Bay State Book Company, North Smithfield, RI, U.S.A.
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Add to basketCondition: good. The book is in good condition with all pages and cover intact, including the dust jacket if originally issued. The spine may show light wear. Pages may contain some notes or highlighting, and there might be a "From the library of" label. Boxed set packaging, shrink wrap, or included media like CDs may be missing.
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Add to basketpaperback. Condition: New. Supporting Bay Area Friends of the Library since 2010. Well packaged and promptly shipped.
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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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Add to basketpaperback. Condition: Gut. 621 Seiten; 9781492045526.3 Gewicht in Gramm: 2.
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Deep Learning for Coders with Fastai and Pytorch : AI Applications Without a PhD
Published by O'reilly Media Aug 2020, 2020
ISBN 10: 1492045527 ISBN 13: 9781492045526
Language: English
£ 63.14
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Add to basketTaschenbuch. Condition: Neu. Neuware - Deep learning has the reputation as an exclusive domain for math PhDs. Not so. With this book, programmers comfortable with Python will learn how to get started with deep learning right away. Using PyTorch and the fastai deep learning library, you'll learn how to train a model to accomplish a wide range of tasks-including computer vision, natural language processing, tabular data, and generative networks. At the same time, you'll dig progressively into deep learning theory so that by the end of the book you'll have a complete understanding of the math behind the library's functions.
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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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Deep Learning for Coders with fastai and PyTorch
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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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Add to basketPaperback. 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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Add to basketpaperback. 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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£ 54.24
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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.
