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portada Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization
Type
Physical Book
Author
Year
2020
Language
English
Pages
788
Format
Hardcover
ISBN13
9781611976052
Edition No.
2

Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization

Jeffrey Humpherys; Tyler J. Jarvis (Author) · · Hardcover

Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization - Jeffrey Humpherys; Tyler J. Jarvis

New Book Imported to Austria
Delivery: 08 Sep - 10 Sep Shipping: 13 to 14 business days.
146,02 €
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146,02 €

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Synopsis "Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization "

In this second book of what will be a four-volume series, the authors present, in a mathematically rigorous way, the essential foundations of both the theory and practice of algorithms, approximation, and optimization―essential topics in modern applied and computational mathematics. This material is the introductory framework upon which algorithm analysis, optimization, probability, statistics, machine learning, and control theory are built. This text gives a unified treatment of several topics that do not usually appear together: the theory and analysis of algorithms for mathematicians and data science students; probability and its applications; the theory and applications of approximation, including Fourier series, wavelets, and polynomial approximation; and the theory and practice of optimization, including dynamic optimization.When used in concert with the free supplemental lab materials, Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization teaches not only the theory but also the computational practice of modern mathematical methods. Exercises and examples build upon each other in a way that continually reinforces previous ideas, allowing students to retain learned concepts while achieving a greater depth. The mathematically rigorous lab content guides students to technical proficiency and answers the age-old question “When am I going to use this?”This textbook is geared toward advanced undergraduate and beginning graduate students in mathematics, data science, or machine learning.

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