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Pattern Recognition and Machine Learning (Information Science and Statistics)
This textbook on Pattern Recognition presents the Bayesian viewpoint, approximate inference algorithms and graphical models to describe probability distributions.
Pattern Recognition and Machine Learning (Information Science and Statistics)
artikal br.: 614469

Pattern Recognition and Machine Learning (Information Science and Statistics)

artikal br.: 614469

RSD 8865

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This textbook on Pattern Recognition presents the Bayesian viewpoint, approximate inference algorithms and graphical models to describe probability distributions.
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What Stands Out

Comprehensive Coverage
This book thoroughly covers foundational concepts in pattern recognition and machine learning, making it an essential resource for both novices and experienced practitioners in the field of data science.
Practical Applications
It includes real-world applications and examples, allowing readers to understand how theoretical concepts are applied in various domains, enhancing their learning experience and practical skills.
Updated Techniques
The text presents the latest developments and techniques in machine learning and pattern recognition, ensuring that readers are well-informed of contemporary advancements that can be applied in modern data challenges.

Детаљи о производу

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Publisher Springer
Publication date August 17, 2006
Language English
Print length 738 pages
ISBN-10 0387310738
ISBN-13 978-0387310732
Item Weight 2.31 pounds (1.05 kg)
Dimensions 7.7 x 1.3 x 10.2 inches (19.6 x 3.3 x 25.9 cm)

Who Should Buy?

Suitable For
  • Graduate Students

    Ideal for graduate students pursuing studies in machine learning and pattern recognition to enhance their academic knowledge.

  • Data Scientists

    Data scientists looking to deepen their understanding of machine learning algorithms and statistical methods will benefit significantly.

  • Research Professionals

    Research professionals in artificial intelligence needing comprehensive insights into advanced topics in pattern recognition and machine learning.

Not Suitable For
  • Beginners

    Not suitable for beginners due to its complex mathematical concepts and advanced technical language.

OPIS PROIZVODA

Pattern Recognition and Machine Learning (Information Science and Statistics)

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Intelligence & Semantics Editorial Review

Pattern Recognition and Machine Learning is a book that is highly recommended for individuals with a solid math background and a strong interest in machine learning. The book is well-structured and contains excellent printing quality. The color figures are helpful, but they do not compensate for the terse prose and large conceptual jumps. The book is not self-contained and may be best used as a supplement to lectures or other textbooks. Some readers may find the problems challenging and the hints confusing. Additionally, there are errors in the book, indicating a shallow understanding of the topics in some cases. Overall, the book is considered to be mediocre and may not be suitable for newcomers to the field.

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  • Received the book earlier than expected
  • Excellent printing quality
  • Well-structured contents

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  • Formatting of maths and code is unreadable

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