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GPU-Accelerated Deep Learning

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GPU-Accelerated Deep Learning
Lowest price (incl. delivery)
60,99 USD
Typical price37,32 PLN
Lowest (90 days)30,79 PLN
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Last updated1 week ago
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2026-08-08 2026-08-15
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Updated AtPrice
2026-08-0831,49
2026-08-1430,79
2026-08-1538,49
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SP SpringerNatureLink Shop INT 41,99 USD 19,00 USD 60,99 USD Available 3 days ago View offer
SP SpringerNatureLink Shop INT 41,99 USD 25,00 USD 66,99 USD Available 3 days ago View offer
SP SpringerNatureLink Shop INT 41,99 USD 25,00 USD 66,99 USD Available 3 days ago View offer
SP SpringerNatureLink Shop INT 41,99 USD 29,00 USD 70,99 USD Available 3 days ago View offer
SP Springer Nature Author 41,99 USD 29,00 USD 70,99 USD Available 1 week ago View offer
SP SpringerNatureLink Shop INT 44,93 EUR free 44,93 EUR Available 3 days ago View offer

Prices and availability may change. Last Updated: 08.08.2026 11:04.

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Explore the convergence of deep learning and GPU technology. This book is a complete guide for those wishing to use GPUs to accelerate AI workflows. The book is meant to make complex concepts understandable, with step-by-step instructions on how to set up and use GPUs in deep learning applications. Starting with an introduction to the fundamentals, you'll dive into progressive topics like Convolutional Neural Networks (CNNs) and sequence models, exploring how GPU optimization boosts performance. Further, you will learn the power of generative models, and take your skills by deploying AI models on edge devices. Finally, you will master the art of scaling and distributed training to handle large datasets and complex tasks efficiently. This book is your roadmap to becoming proficient in deep learning and harnessing the full potential of GPUs. What You Will Learn: How to apply deep learning techniques on GPUs to solve challenging AI problems. Optimizing neural networks for faster training and inference on GPUs Integration of GPUs with Microsoft Copilots Implementing VAEs (Variational Autoencoders) with TensorFlow and PyTorch Who This Book Is For: Industry IT professionals in AI. Students pursuing undergraduate and postgraduate degrees in Engineering, Computer Science, Data Science.

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