Mukesh raghuwanshi (34 résultats)

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Etat : New.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

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Etat : New. 1st edition NO-PA16APR2015-KAP.

Paperback. Etat : Brand New. 168 pages. 8.66x5.91x0.38 inches. In Stock.

Etat : New. Dr. M. M. Raghuwanshi is the Dean of Engineering at S.B.Jain Institute of Technology Management and Research, Nagpur, India.Dr. Pradnya Borkar is an Associate Professor at the Department of Computer Science and Engineering and R&amp.

Taschenbuch. Etat : Neu. Neuware - Parallel and High-Performance Computing in Artificial Intelligence explores high-performance architectures for data-intensive applications as well as efficient analytical strategies to speed up data processing and applications in automation, machine learning, deep learning, healthcare, bioinformatics, natural language processing (NLP), and vision intelligence.The book's two major themes are high-performance computing (HPC) architecture and techniques and their application in artificial intelligence. Highlights include: - HPC use cases, application programming interfaces (APIs), and applications - Parallelization techniques - HPC for machine learning - Implementation of parallel computing with AI in big data analytics - HPC with AI in healthcare systems - AI in industrial automation Coverage of HPC architecture and techniques includes multicore architectures, parallel-computing techniques, and APIs, as well as dependence analysis for parallel computing. The book also covers hardware acceleration techniques, including those for GPU acceleration to power big data systems.As AI is increasingly being integrated into HPC applications, the book explores emerging and practical applications in such domains as healthcare, agriculture, bioinformatics, and industrial automation. It illustrates technologies and methodologies to boost the velocity and scale of AI analysis for fast discovery. Data scientists and researchers can benefit from the book's discussion on AI-based HPC applications that can process higher volumes of data, provide more realistic simulations, and guide more accurate predictions. The book also focuses on deep learning and edge computing methodologies with HPC and presents recent research on methodologies and applications of HPC in AI.…

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Etat : As New. Unread book in perfect condition.

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Etat : As New. Unread book in perfect condition.

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Etat : New. In English.

HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.

HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.

Etat : New.

Hardback. Etat : New. Parallel and High-Performance Computing in Artificial Intelligence explores high-performance architectures for data-intensive applications as well as efficient analytical strategies to speed up data processing and applications in automation, machine learning, deep learning, healthcare, bioinformatics, natural language processing (NLP), and vision intelligence.The book's two major themes are high-performance computing (HPC) architecture and techniques and their application in artificial intelligence. Highlights include:HPC use cases, application programming interfaces (APIs), and applicationsParallelization techniquesHPC for machine learningImplementation of parallel computing with AI in big data analyticsHPC with AI in healthcare systemsAI in industrial automationCoverage of HPC architecture and techniques includes multicore architectures, parallel-computing techniques, and APIs, as well as dependence analysis for parallel computing. The book also covers hardware acceleration techniques, including those for GPU acceleration to power big data systems.As AI is increasingly being integrated into HPC applications, the book explores emerging and practical applications in such domains as healthcare, agriculture, bioinformatics, and industrial automation. It illustrates technologies and methodologies to boost the velocity and scale of AI analysis for fast discovery. Data scientists and researchers can benefit from the book's discussion on AI-based HPC applications that can process higher volumes of data, provide more realistic simulations, and guide more accurate predictions. The book also focuses on deep learning and edge computing methodologies with HPC and presents recent research on methodologies and applications of HPC in AI. …

Hardcover. Etat : Brand New. 336 pages. 9.18x6.12x9.21 inches. In Stock.

Hardback. Etat : New. Parallel and High-Performance Computing in Artificial Intelligence explores high-performance architectures for data-intensive applications as well as efficient analytical strategies to speed up data processing and applications in automation, machine learning, deep learning, healthcare, bioinformatics, natural language processing (NLP), and vision intelligence.The book's two major themes are high-performance computing (HPC) architecture and techniques and their application in artificial intelligence. Highlights include:HPC use cases, application programming interfaces (APIs), and applicationsParallelization techniquesHPC for machine learningImplementation of parallel computing with AI in big data analyticsHPC with AI in healthcare systemsAI in industrial automationCoverage of HPC architecture and techniques includes multicore architectures, parallel-computing techniques, and APIs, as well as dependence analysis for parallel computing. The book also covers hardware acceleration techniques, including those for GPU acceleration to power big data systems.As AI is increasingly being integrated into HPC applications, the book explores emerging and practical applications in such domains as healthcare, agriculture, bioinformatics, and industrial automation. It illustrates technologies and methodologies to boost the velocity and scale of AI analysis for fast discovery. Data scientists and researchers can benefit from the book's discussion on AI-based HPC applications that can process higher volumes of data, provide more realistic simulations, and guide more accurate predictions. The book also focuses on deep learning and edge computing methodologies with HPC and presents recent research on methodologies and applications of HPC in AI. …

Paperback. Etat : new. Paperback. Parallel and High-Performance Computing in Artificial Intelligence explores high-performance architectures for data-intensive applications as well as efficient analytical strategies to speed up data processing and applications in automation, machine learning, deep learning, healthcare, bioinformatics, natural language processing (NLP), and vision intelligence.The books two major themes are high-performance computing (HPC) architecture and techniques and their application in artificial intelligence. Highlights include:HPC use cases, application programming interfaces (APIs), and applicationsParallelization techniquesHPC for machine learningImplementation of parallel computing with AI in big data analyticsHPC with AI in healthcare systemsAI in industrial automationCoverage of HPC architecture and techniques includes multicore architectures, parallel-computing techniques, and APIs, as well as dependence analysis for parallel computing. The book also covers hardware acceleration techniques, including those for GPU acceleration to power big data systems.As AI is increasingly being integrated into HPC applications, the book explores emerging and practical applications in such domains as healthcare, agriculture, bioinformatics, and industrial automation. It illustrates technologies and methodologies to boost the velocity and scale of AI analysis for fast discovery. Data scientists and researchers can benefit from the books discussion on AI-based HPC applications that can process higher volumes of data, provide more realistic simulations, and guide more accurate predictions. The book also focuses on deep learning and edge computing methodologies with HPC and presents recent research on methodologies and applications of HPC in AI. The book explores high-performance architectures for data-intensive applications, as well as efficient analytical strategies, to speed up data processing in applications in automation, machine learning, deep learning, bioinformatics, natural language processing, and vision intelligence. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Prakashkumar Rana DiptiDr. Dipti Prakashkumar Rana, is a faculty member at Computer Engineering Department, Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat, India. She is having teaching experience of more than 17 . …

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mehta RupaDr. Rupa Mehta obtained her M.Tech and PhD from SVNIT, Surat (Institute of National Importance). She is currently working as a Head and Associate Professor at Department of Computer Engineering, SVNIT, Surat having more tha.…

Etat : New. Print on Demand.

Paperback. Etat : new. Paperback. Parallel and High-Performance Computing in Artificial Intelligence explores high-performance architectures for data-intensive applications as well as efficient analytical strategies to speed up data processing and applications in automation, machine learning, deep learning, healthcare, bioinformatics, natural language processing (NLP), and vision intelligence.The books two major themes are high-performance computing (HPC) architecture and techniques and their application in artificial intelligence. Highlights include:HPC use cases, application programming interfaces (APIs), and applicationsParallelization techniquesHPC for machine learningImplementation of parallel computing with AI in big data analyticsHPC with AI in healthcare systemsAI in industrial automationCoverage of HPC architecture and techniques includes multicore architectures, parallel-computing techniques, and APIs, as well as dependence analysis for parallel computing. The book also covers hardware acceleration techniques, including those for GPU acceleration to power big data systems.As AI is increasingly being integrated into HPC applications, the book explores emerging and practical applications in such domains as healthcare, agriculture, bioinformatics, and industrial automation. It illustrates technologies and methodologies to boost the velocity and scale of AI analysis for fast discovery. Data scientists and researchers can benefit from the books discussion on AI-based HPC applications that can process higher volumes of data, provide more realistic simulations, and guide more accurate predictions. The book also focuses on deep learning and edge computing methodologies with HPC and presents recent research on methodologies and applications of HPC in AI. The book explores high-performance architectures for data-intensive applications, as well as efficient analytical strategies, to speed up data processing in applications in automation, machine learning, deep learning, bioinformatics, natural language processing, and vision intelligence. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Etat : New. PRINT ON DEMAND.