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books
| book details |
Advanced Methods for Optimizing and Accelerating Deep Learning Models
Edited by Patrick Siarry, Edited by Rahma Fourati, Edited by Jihene Tmamna, Edited by Asma Baghdadi
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| on special |
normal price: R 6 778.95
Price: R 6 440.95
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| book description |
Advanced Optimization and Acceleration Techniques for Deep Learning Models provides a comprehensive guide to enhancing deep learning models' efficiency, scalability, and performance, including large language models (LLMs). As AI systems grow in complexity, optimizing their training and deployment has become critical for achieving higher accuracy, faster inference, and reduced computational costs. This book explores cutting-edge optimization strategies, from gradient descent refinements and hyperparameter tuning to model compression, pruning, and hardware acceleration. AI is evolving rapidly, but existing deep learning resources often focus on building models rather than optimizing them for efficiency and scalability. As deep learning applications expand into cloud computing, edge AI, and real-time decision-making, a dedicated resource on optimization is essential. This book addresses this gap by providing a structured approach to making deep learning networks faster, more cost-effective, and more sustainable.
| product details |
Normally shipped |
Publisher | Elsevier Science & Technology
Published date | 1 Feb 2027
Language |
Format | Paperback / softback
Pages | 200
Dimensions | 235 x 191 x 0mm (L x W x H)
Weight | 450g
ISBN | 978-0-4434-8495-7
Readership Age |
BISAC | computers / artificial intelligence
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This is indeed a story of mercy and the redemption it offers.
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Victor Frankenstein driven by the mad dream of creating his own creature, experiments with alchemy and science to build a monster stitched together from dead remains.
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Katie Daysh
Paperback / softback
384 pages
was: R 295.95
now: R 259.95
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