Da: Dream Books Co., Denver, CO, U.S.A.
Condizione: acceptable. This copy has clearly been enjoyedâ"expect noticeable shelf wear and some minor creases to the cover. Binding is strong, and all pages are legible. May contain previous library markings or stamps.
Da: Dream Books Co., Denver, CO, U.S.A.
Condizione: good. Gently used with minimal wear on the corners and cover. A few pages may contain light highlighting or writing, but the text remains fully legible. Dust jacket may be missing, and supplemental materials like CDs or codes may not be included. May be ex-library with library markings. Ships promptly!
Da: World of Books (was SecondSale), Montgomery, IL, U.S.A.
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Da: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Condizione: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.
Condizione: good. Book shows general signs of use and handling. May have light wear on the cover or edges and minimal writing or highlighting. Binding remains tight, and pages are clean and readable.
Da: HPB-Red, Dallas, TX, U.S.A.
Paperback. Condizione: 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!
Da: HPB-Ruby, Dallas, TX, U.S.A.
paperback. Condizione: 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!
Da: ThriftBooks-Atlanta, AUSTELL, GA, U.S.A.
Paperback. Condizione: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: Manning Publications, New York, 2020
ISBN 10: 1617295264 ISBN 13: 9781617295263
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you, and your deep learning skills, become more sophisticated. Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch. This book takes you into a fascinating case study: building an algorithm capable of detecting malignant lung tumors using CT scans. As the authors guide you through this real example, you'll discover just how effective and fun PyTorch can be. Key features Using the PyTorch tensor API Understanding automatic differentiation in PyTorch Training deep neural networks Monitoring training and visualizing results Interoperability with NumPy Audience Written for developers with some knowledge of Python as well as basic linear algebra skills. Some understanding of deep learning will be helpful, however no experience with PyTorch or other deep learning frameworks is required. About the technology PyTorch is a machine learning framework with a strong focus on deep neural networks. Because it emphasizes GPU-based acceleration, PyTorch performs exceptionally well on readily-available hardware and scales easily to larger systems. Eli Stevens has worked in Silicon Valley for the past 15 years as a software engineer, and the past 7 years as Chief Technical Officer of a startup making medical device software. Luca Antiga is co-founder and CEO of an AI engineering company located in Bergamo, Italy, and a regular contributor to PyTorch. "For Python programmers with an interest in machine learning"--Back cover. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: upickbook, Daly City, CA, U.S.A.
paperback. Condizione: New.
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Aggiungi al carrelloPaperback. Condizione: New. Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you, and your deep learning skills, become more sophisticated. Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch. This book takes you into a fascinating case study: building an algorithm capable of detecting malignant lung tumors using CT scans. As the authors guide you through this real example, you'll discover just how effective and fun PyTorch can be. Key features . Using the PyTorch tensor API . Understanding automatic differentiation in PyTorch . Training deep neural networks . Monitoring training and visualizing results . Interoperability with NumPy Audience Written for developers with some knowledge of Python as well as basic linear algebra skills. Some understanding of deep learning will be helpful, however no experience with PyTorch or other deep learning frameworks is required. About the technology PyTorch is a machine learning framework with a strong focus on deep neural networks. Because it emphasizes GPU-based acceleration, PyTorch performs exceptionally well on readily-available hardware and scales easily to larger systems. Eli Stevens has worked in Silicon Valley for the past 15 years as a software engineer, and the past 7 years as Chief Technical Officer of a startup making medical device software. Luca Antiga is co-founder and CEO of an AI engineering company located in Bergamo, Italy, and a regular contributor to PyTorch.
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Aggiungi al carrellopaperback. Condizione: New.
Paperback. Condizione: New. Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you, and your deep learning skills, become more sophisticated. Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch. This book takes you into a fascinating case study: building an algorithm capable of detecting malignant lung tumors using CT scans. As the authors guide you through this real example, you'll discover just how effective and fun PyTorch can be. Key features . Using the PyTorch tensor API . Understanding automatic differentiation in PyTorch . Training deep neural networks . Monitoring training and visualizing results . Interoperability with NumPy Audience Written for developers with some knowledge of Python as well as basic linear algebra skills. Some understanding of deep learning will be helpful, however no experience with PyTorch or other deep learning frameworks is required. About the technology PyTorch is a machine learning framework with a strong focus on deep neural networks. Because it emphasizes GPU-based acceleration, PyTorch performs exceptionally well on readily-available hardware and scales easily to larger systems. Eli Stevens has worked in Silicon Valley for the past 15 years as a software engineer, and the past 7 years as Chief Technical Officer of a startup making medical device software. Luca Antiga is co-founder and CEO of an AI engineering company located in Bergamo, Italy, and a regular contributor to PyTorch.
Da: Ria Christie Collections, Uxbridge, Regno Unito
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Prima edizione
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Aggiungi al carrelloCondizione: New. 2020. 1st Edition. Paperback. . . . . .
Da: Revaluation Books, Exeter, Regno Unito
EUR 61,44
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Aggiungi al carrelloPaperback. Condizione: Brand New. 450 pages. 9.00x7.25x1.00 inches. In Stock.
Da: Revaluation Books, Exeter, Regno Unito
EUR 67,41
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Aggiungi al carrelloPaperback. Condizione: Brand New. 450 pages. 9.00x7.25x1.00 inches. In Stock.
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Aggiungi al carrelloCondizione: New. Über den AutorEli Stevens has worked in Silicon Valley for the past 15 years as a software engineer, and the past 7 years as Chief Technical Officer of a startup making medical device software.Klappentextrn.
Paperback. Condizione: New. Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you, and your deep learning skills, become more sophisticated. Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch. This book takes you into a fascinating case study: building an algorithm capable of detecting malignant lung tumors using CT scans. As the authors guide you through this real example, you'll discover just how effective and fun PyTorch can be. Key features . Using the PyTorch tensor API . Understanding automatic differentiation in PyTorch . Training deep neural networks . Monitoring training and visualizing results . Interoperability with NumPy Audience Written for developers with some knowledge of Python as well as basic linear algebra skills. Some understanding of deep learning will be helpful, however no experience with PyTorch or other deep learning frameworks is required. About the technology PyTorch is a machine learning framework with a strong focus on deep neural networks. Because it emphasizes GPU-based acceleration, PyTorch performs exceptionally well on readily-available hardware and scales easily to larger systems. Eli Stevens has worked in Silicon Valley for the past 15 years as a software engineer, and the past 7 years as Chief Technical Officer of a startup making medical device software. Luca Antiga is co-founder and CEO of an AI engineering company located in Bergamo, Italy, and a regular contributor to PyTorch.
Lingua: Inglese
Editore: Manning Publications Okt 2020, 2020
ISBN 10: 1617295264 ISBN 13: 9781617295263
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 58,73
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware - Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you, and your deep learning skills, become more sophisticated.Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch. This book takes you into a fascinating case study: building an algorithm capable of detecting malignant lung tumors using CT scans. As the authors guide you through this real example, you'll discover just how effective and fun PyTorch can be. Key features Using the PyTorch tensor API Understanding automatic differentiation in PyTorch Training deep neural networks Monitoring training and visualizing results Interoperability with NumPyAudienceWritten for developers with some knowledge of Python as well as basic linear algebra skills. Some understanding of deep learning will be helpful, however no experience with PyTorch or other deep learning frameworks is required.About the technologyPyTorch is a machine learning framework with a strong focus on deep neural networks. Because it emphasizes GPU-based acceleration, PyTorch performs exceptionally well on readily-available hardware and scales easily to larger systems.
Lingua: Inglese
Editore: Manning Publications, New York, 2020
ISBN 10: 1617295264 ISBN 13: 9781617295263
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 96,09
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you, and your deep learning skills, become more sophisticated. Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch. This book takes you into a fascinating case study: building an algorithm capable of detecting malignant lung tumors using CT scans. As the authors guide you through this real example, you'll discover just how effective and fun PyTorch can be. Key features Using the PyTorch tensor API Understanding automatic differentiation in PyTorch Training deep neural networks Monitoring training and visualizing results Interoperability with NumPy Audience Written for developers with some knowledge of Python as well as basic linear algebra skills. Some understanding of deep learning will be helpful, however no experience with PyTorch or other deep learning frameworks is required. About the technology PyTorch is a machine learning framework with a strong focus on deep neural networks. Because it emphasizes GPU-based acceleration, PyTorch performs exceptionally well on readily-available hardware and scales easily to larger systems. Eli Stevens has worked in Silicon Valley for the past 15 years as a software engineer, and the past 7 years as Chief Technical Officer of a startup making medical device software. Luca Antiga is co-founder and CEO of an AI engineering company located in Bergamo, Italy, and a regular contributor to PyTorch. "For Python programmers with an interest in machine learning"--Back cover. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
EUR 54,25
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Aggiungi al carrelloPaperback. Condizione: New. Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you, and your deep learning skills, become more sophisticated. Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch. This book takes you into a fascinating case study: building an algorithm capable of detecting malignant lung tumors using CT scans. As the authors guide you through this real example, you'll discover just how effective and fun PyTorch can be. Key features . Using the PyTorch tensor API . Understanding automatic differentiation in PyTorch . Training deep neural networks . Monitoring training and visualizing results . Interoperability with NumPy Audience Written for developers with some knowledge of Python as well as basic linear algebra skills. Some understanding of deep learning will be helpful, however no experience with PyTorch or other deep learning frameworks is required. About the technology PyTorch is a machine learning framework with a strong focus on deep neural networks. Because it emphasizes GPU-based acceleration, PyTorch performs exceptionally well on readily-available hardware and scales easily to larger systems. Eli Stevens has worked in Silicon Valley for the past 15 years as a software engineer, and the past 7 years as Chief Technical Officer of a startup making medical device software. Luca Antiga is co-founder and CEO of an AI engineering company located in Bergamo, Italy, and a regular contributor to PyTorch.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Deep Learning with PyTorch | Eli Stevens (u. a.) | Taschenbuch | Kartoniert / Broschiert | Englisch | 2020 | Manning Publications | EAN 9781617295263 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.