Isbn: 9780367575632 - numerical algorithms: methods for computer vision, machine learning, and graphics (17 risultati)

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New. pp. 400.

Condizione: New.

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

Condizione: As New. Unread book in perfect condition.

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

Condizione: New.

Condizione: New. pp. 400.

Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.

Condizione: New. pp. 400.

Condizione: New. In English.

Paperback. Condizione: New. Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into 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. It incorporates cases from computer science research and practice, accompanied by highlights from in-depth literature on each subtopic. Comprehensive end-of-chapter exercises encourage critical thinking and build students' intuition while introducing extensions of the basic material.The text is designed for advanced undergraduate and beginning graduate students in computer science and related fields with experience in calculus and linear algebra. For students with a background in discrete mathematics, the book includes some reminders of relevant continuous mathematical background. …

Paperback. Condizione: Brand New. 400 pages. 10.00x7.01x1.46 inches. In Stock.

Paperback. Condizione: New. Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into 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. It incorporates cases from computer science research and practice, accompanied by highlights from in-depth literature on each subtopic. Comprehensive end-of-chapter exercises encourage critical thinking and build students' intuition while introducing extensions of the basic material.The text is designed for advanced undergraduate and beginning graduate students in computer science and related fields with experience in calculus and linear algebra. For students with a background in discrete mathematics, the book includes some reminders of relevant continuous mathematical background. …

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Justin Solomon is an assistant professor in the Department of Electrical Engineering and Computer Science at MIT, where he studies problems in shape analysis, machine learning, and graphics from a geometric perspective. He received a PhD.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into 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. It incorporates cases from computer science research and practice, accompanied by highlights from in-depth literature on each subtopic. Comprehensive end-of-chapter exercises encourage critical thinking and build students' intuition while introducing extensions of the basic material.The text is designed for advanced undergraduate and beginning graduate students in computer science and related fields with experience in calculus and linear algebra. For students with a background in discrete mathematics, the book includes some reminders of relevant continuous mathematical background.…