This book is ideal for developers and students who want to build deep learning models with PyTorch, combining flexibility, control, and real-world performance.
You will learn to apply modern techniques to design, train, and scale robust neural networks in real-world environments, covering everything from fundamentals to advanced architectures.
Includes:
• Tensor manipulation and Autograd usage
• Modular neural network construction with torch.nn
• Training with DataLoader, optimizers, and loss functions
• Practical application with CNNs, RNNs, Transformers, and GANs
• Integration with PyTorch Lightning, TorchScript, and model export
• Real-world projects with NLP, computer vision, IoT, and cloud deployment
By the end, you will master PyTorch as a professional tool to design scalable AI solutions with technical precision and development agility.
ytorch, deep learning, neural networks, torch.nn, autograd, distributed training, cnn, rnn, transformers, deployment
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Paperback. Etat : new. Paperback. This book is ideal for developers and students who want to build deep learning models with PyTorch, combining flexibility, control, and real-world performance.You will learn to apply modern techniques to design, train, and scale robust neural networks in real-world environments, covering everything from fundamentals to advanced architectures.Includes: - Tensor manipulation and Autograd usage- Modular neural network construction with torch.nn- Training with DataLoader, optimizers, and loss functions- Practical application with CNNs, RNNs, Transformers, and GANs- Integration with PyTorch Lightning, TorchScript, and model export- Real-world projects with NLP, computer vision, IoT, and cloud deploymentBy the end, you will master PyTorch as a professional tool to design scalable AI solutions with technical precision and development agility. ytorch, deep learning, neural networks, torch.nn, autograd, distributed training, cnn, rnn, transformers, deployment This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798312289015
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Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L0-9798312289015
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 50019632-n
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 50019632
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Vendeur : CitiRetail, Stevenage, Royaume-Uni
Paperback. Etat : new. Paperback. This book is ideal for developers and students who want to build deep learning models with PyTorch, combining flexibility, control, and real-world performance.You will learn to apply modern techniques to design, train, and scale robust neural networks in real-world environments, covering everything from fundamentals to advanced architectures.Includes: - Tensor manipulation and Autograd usage- Modular neural network construction with torch.nn- Training with DataLoader, optimizers, and loss functions- Practical application with CNNs, RNNs, Transformers, and GANs- Integration with PyTorch Lightning, TorchScript, and model export- Real-world projects with NLP, computer vision, IoT, and cloud deploymentBy the end, you will master PyTorch as a professional tool to design scalable AI solutions with technical precision and development agility. ytorch, deep learning, neural networks, torch.nn, autograd, distributed training, cnn, rnn, transformers, deployment This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798312289015
Quantité disponible : 1 disponible(s)