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Building DeepSeek AI Models: Architecture, Implementation, and Optimization (Advanced Topics in Machine Learning) - Softcover
Synopsis
This book offers an in-depth exploration of the design, implementation, and optimization of DeepSeek AI models, blending theoretical rigor with advanced engineering insights. It unravels the complexities of cutting-edge deep learning techniques—including transformer architectures, Mixture-of-Experts, and reinforcement learning fine-tuning—equipping researchers and engineers with the expertise to build, scale, and deploy large language models with precision and efficiency.
With a strong focus on algorithmic advancements and hardware optimizations, this guide addresses the pressing challenges of training ultra-large models, ensuring efficiency, scalability, and reliability. Rich with practical blueprints and real-world case studies, it showcases applications from code intelligence to multi-step reasoning, offering a comprehensive roadmap for AI practitioners.
By integrating discussions on data preprocessing, distributed training, and custom GPU optimization libraries, this book serves as an indispensable resource for those pushing the boundaries of open-source AI research—fostering innovation, collaboration, and the future of large-scale deep learning.
"synopsis" may belong to another edition of this title.
- PublisherIndependently published
- Publication date2025
- ISBN 13 9798313438481
- BindingPaperback
- LanguageEnglish
- Number of pages223
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Building DeepSeek AI Models: Architecture, Implementation, and Optimization (Advanced Topics in Machine Learning)
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Building DeepSeek AI Models (Paperback)
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Paperback. Condition: new. Paperback. This book offers an in-depth exploration of the design, implementation, and optimization of DeepSeek AI models, blending theoretical rigor with advanced engineering insights. It unravels the complexities of cutting-edge deep learning techniques-including transformer architectures, Mixture-of-Experts, and reinforcement learning fine-tuning-equipping researchers and engineers with the expertise to build, scale, and deploy large language models with precision and efficiency. With a strong focus on algorithmic advancements and hardware optimizations, this guide addresses the pressing challenges of training ultra-large models, ensuring efficiency, scalability, and reliability. Rich with practical blueprints and real-world case studies, it showcases applications from code intelligence to multi-step reasoning, offering a comprehensive roadmap for AI practitioners. By integrating discussions on data preprocessing, distributed training, and custom GPU optimization libraries, this book serves as an indispensable resource for those pushing the boundaries of open-source AI research-fostering innovation, collaboration, and the future of large-scale deep learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798313438481
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Building DeepSeek AI Models: Architecture, Implementation, and Optimization (Advanced Topics in Machine Learning)
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Building DeepSeek AI Models (Paperback)
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Paperback. Condition: new. Paperback. This book offers an in-depth exploration of the design, implementation, and optimization of DeepSeek AI models, blending theoretical rigor with advanced engineering insights. It unravels the complexities of cutting-edge deep learning techniques-including transformer architectures, Mixture-of-Experts, and reinforcement learning fine-tuning-equipping researchers and engineers with the expertise to build, scale, and deploy large language models with precision and efficiency. With a strong focus on algorithmic advancements and hardware optimizations, this guide addresses the pressing challenges of training ultra-large models, ensuring efficiency, scalability, and reliability. Rich with practical blueprints and real-world case studies, it showcases applications from code intelligence to multi-step reasoning, offering a comprehensive roadmap for AI practitioners. By integrating discussions on data preprocessing, distributed training, and custom GPU optimization libraries, this book serves as an indispensable resource for those pushing the boundaries of open-source AI research-fostering innovation, collaboration, and the future of large-scale deep learning. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798313438481
Quantity: 1 available