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Machine Learning: A Bayesian and Optimization Perspective
a wonderful book, up to date and rich in detail
Machine Learning: A Bayesian and Optimization Perspective
Item #: 1226394

Machine Learning: A Bayesian and Optimization Perspective

Item #: 1226394

€ 216

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What Stands Out

Comprehensive Framework
Offers a thorough introduction to machine learning through a unified Bayesian and optimization lens, making complex concepts accessible to both beginners and advanced learners.
Research-Driven Insights
Incorporates the latest research and practical applications, equipping readers with knowledge that bridges theory and real-world practice in the rapidly evolving field of machine learning.
Practical Examples
Includes practical examples and exercises that enhance learning by allowing readers to apply theoretical concepts, making it an ideal resource for students and professionals alike.

Product Details

Shop the globally recognized book 'Machine Learning: A Bayesian and Optimization Perspective' on Ubuy Italy. Perfect for advanced courses in machine learning and suitable for beginners and seasoned researchers. Get your copy now!
  • Well-organized and suitable for advanced graduate and postgraduate courses
  • Covers classical regression and classification techniques, as well as more recent ones such as sparse modeling, convex optimization, Bayesian learning, graphical models, and neural networks
  • Provides insight and detail, making it highly relevant in the deep learning era
  • Chapters are written in a self-consistent way to accommodate students with varying backgrounds
  • Book presents major machine learning methods from statistics, signal processing, and computer science with physical reasoning behind the mathematics
  • Comes with MATLAB code for main algorithms available on an accompanying website
Publisher Academic Press
Publication date April 10, 2015
Edition 1st
Language English
Print length 1062 pages
ISBN-10 0128015225
ISBN-13 978-0128015223
Item Weight 5.16 pounds (2.34 kg)
Dimensions 7.75 x 2 x 9.5 inches (19.7 x 5.1 x 24.1 cm)

Who Should Buy?

Suitable For
  • Graduate Students

    Ideal for graduate students pursuing advanced courses in machine learning, statistics, and Bayesian inference methodologies.

  • Data Scientists

    Useful for data scientists who need a solid foundation in Bayesian approaches and optimization techniques for model building.

  • Researchers

    Great resource for researchers focusing on cutting-edge machine learning methodologies, including Bayesian models and optimization approaches.

Not Suitable For
  • Beginners

    Not suitable for beginners due to its advanced concepts, requiring pre-existing knowledge of statistics and machine learning.

Product Description

Machine Learning: A Bayesian and Optimization Perspective

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Intelligence & Semantics Editorial Review

Machine Learning: A Bayesian and Optimization Perspective is an extensive work published by Academic Press on April 10, 2015, spanning 1062 pages. The book cohesively integrates machine learning and parameter estimation into a unified framework, making it an excellent resource for professional engineers and academics alike. Reviewers commend its focus on practical applications rather than overly theoretical discussions, highlighting its accessibility and well-structured chapters that explain complex ideas clearly. Sections on modern topics such as deep learning and Bayesian non-parametric models make this book a comprehensive guide for both practitioners and students in the rapidly evolving field of machine learning.

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Pros

  • Comprehensive coverage of both classic and advanced topics
  • Well-structured and easy to read
  • Strong focus on practical applications
  • Includes references for further reading
  • Highly regarded by professionals and academics

Cons

  • The book is quite dense and lengthy, requiring commitment

Product Price History

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