Articoli correlati a Deep Learning With Pytorch: Build, Train, and Tune...
- EditoreManning Pubns Co
- Data di pubblicazione2020
- ISBN 10 1617295264
- ISBN 13 9781617295263
- RilegaturaCopertina flessibile
- LinguaInglese
- Numero edizione1
- Numero di pagine450
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Deep Learning with PyTorch: Build, train, and tune neural networks using Python tools
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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! Codice articolo S_432115469
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Deep Learning with PyTorch: Build, train, and tune neural networks using Python tools
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Condizione: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. Codice articolo 00082283049
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Deep Learning with PyTorch: Build train and tune neural networks using Python tools
Da: Follow Books, SOUTHFIELD, MI, U.S.A.
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Condizione: New. New Book. Codice articolo 1617295264-TUX
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Deep Learning with PyTorch Format: Paperback
Da: INDOO, Avenel, NJ, U.S.A.
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Condizione: New. Codice articolo 9781617295263
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Deep Learning with PyTorch Format: Paperback
Editore:
Simon and Schuster, 2020
ISBN 10: 1617295264
ISBN 13: 9781617295263
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Da: INDOO, Avenel, NJ, U.S.A.
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Deep Learning with Pytorch (Paperback or Softback)
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Manning Publications 8/4/2020, 2020
ISBN 10: 1617295264
ISBN 13: 9781617295263
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Da: BargainBookStores, Grand Rapids, MI, U.S.A.
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Paperback or Softback. Condizione: New. Deep Learning with Pytorch 1.9. Book. Codice articolo BBS-9781617295263
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Deep Learning with PyTorch: Build, train, and tune neural networks using Python tools
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Condizione: New. Codice articolo ABLIING23Mar2811580147440
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Deep Learning with PyTorch: Build, train, and tune neural networks using Python tools
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Condizione: New. Codice articolo I-9781617295263
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Deep Learning with PyTorch (Paperback)
Editore:
Manning Publications, New York, 2020
ISBN 10: 1617295264
ISBN 13: 9781617295263
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Da: Grand Eagle Retail, Fairfield, OH, U.S.A.
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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. Codice articolo 9781617295263
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Deep Learning with PyTorch
Da: PBShop.store US, Wood Dale, IL, U.S.A.
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo IB-9781617295263
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