Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics

Introducing a new approach to numerical analysis for modern computer scientists, this textbook introduces numerical modeling and algorithmic design from a practical perspective and provides information on the theoretical tools needed to support these skills.

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Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Charts introduces a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational activities, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic design from a practical perspective and provides information on the theoretical tools needed to support these skills. .

The book covers a wide range of topics, from numerical linear algebra to optimization and differential equations, focusing on real-world motivation and unifying themes. Incorporates cases from computer science research and practice, accompanied by detailed literature highlights on each subtopic. Comprehensive end-of-chapter exercises encourage critical thinking and develop students’ intuition as they introduce extensions to the core material. The text is designed for advanced undergraduates and recent graduates in computer science and related fields with a background in calculus and linear algebra. For students with a background in discrete mathematics, the book includes some references to the relevant continuing mathematical background.

 

Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics PDF


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