Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)
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Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)
Nº de artículo: 41593414

Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)

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Nº de artículo: 41593414

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What Stands Out

Comprehensive Coverage
This book provides an extensive overview of Gaussian processes, making complex concepts accessible for practitioners and researchers, ultimately enhancing users' understanding of machine learning applications.
Practical Applications
Real-world examples illustrate how Gaussian processes can be applied, showcasing their versatility in solving diverse problems in machine learning, which sets it apart from theoretical-focused resources.
Expert Insights
Authored by leading experts in the field, the book includes valuable insights and methodologies, ensuring readers gain cutting-edge knowledge and practical skills that add immense value to their professional toolkit.

Detalles de producto

Shop the Gaussian Processes for Machine Learning book and improve your understanding of adaptive computation and machine learning. Fast delivery on Ubuy Puerto Rico.
Publisher The MIT Press
Publication date November 23, 2005
Language English
Print length 272 pages
ISBN-10 9780262182539
ISBN-13 978-0262182539
Item Weight 1.62 pounds (730 grams)
Reading age 18 years and up
Dimensions 10.22 x 8.26 x 0.73 inches (26 x 21 x 1.9 cm)
Grade level 12 and up

Who Should Buy?

Suitable For
  • Data Scientists

    Ideal for data scientists seeking to leverage advanced probabilistic modeling techniques for real-world applications.

  • Research Academics

    A valuable resource for academics researching machine learning, offering theoretical foundations and practical insights into Gaussian processes.

  • Graduate Students

    Perfect for graduate students studying machine learning, providing comprehensive content that's both theoretical and practical.

Not Suitable For
  • Beginners

    Not suitable for beginners due to its complex mathematical content and prerequisite knowledge of machine learning concepts.

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Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)

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Intelligence & Semantics Editorial Review

This book on Gaussian Processes (GP) is highly recommended for academic researchers working on GP related projects. However, the book is not just about GP, it also includes a lot of general Machine Learning (ML) details. The book is technical but also does a great job explaining how GP fits into the big picture of the last few decades in the ML field and how it relates to Support Vector Machines (SVM) and Neural Networks. The explanations are clear and to the point. Although it is not a cookbook on GP, it is a valuable reference. The book is well-edited and comes in hardcover - a great price for what it offers.

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ventajas

  • Valuable reference for GP related research
  • Includes general ML details
  • Clear and concise explanations
  • Well-edited hardcover book
  • Affordable price

Contras

  • Highly technical, may not be suitable for beginners

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