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Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization
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Foundations of Applied Mathematics Volume 2 provides a unified treatment of algorithms, approximation, and optimization essential for modern applied and computational mathematics.
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產品詳情
| Publisher | SIAM - Society for Industrial and Applied Mathematics |
| Publication date | March 11, 2020 |
| Edition | Second |
| Language | English |
| Print length | 788 pages |
| ISBN-10 | 1611976057 |
| ISBN-13 | 978-1611976052 |
| Item Weight | 4.06 pounds (1.84 kg) |
| Dimensions | 10.43 x 2.28 x 7.48 inches (26.5 x 5.8 x 19 cm) |
產品描述
Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization
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Functional Analysis Editorial Review
**** This textbook has garnered positive reception among students and professionals alike, highlighting its value in the fields of applied mathematics, optimization, and algorithms. Reviewers praise the book for its comprehensive approach, covering a vast array of fundamental topics crucial for anyone aiming to excel in algorithmic problem-solving, including future careers as software engineers or data scientists. Its clarity and well-structured content make complex concepts accessible, facilitating a deeper understanding of essential principles. Additionally, many users share their firsthand experiences correlating their academic pursuits with this textbook, noting that it serves as an excellent companion to associated courses and is often referenced for further research and exploration. At an affordable price point of under $100, the book is perceived as a treasure trove of knowledge that every mathematics student should have access to. In summary, this textbook stands out for its informative and well-organized content, making it an indispensable resource for those studying applied mathematics. **
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優點
- Comprehensive coverage of foundational topics in optimization and algorithms
- Well-written and accessible, aiding understanding of complex concepts
- Valuable for multiple career paths including software engineering and data science
- Highly regarded by students who have taken courses associated with the textbook
- Affordable price for the extensive knowledge provided
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特色和優勢
- Provides essential theory and practice for algorithms, approximation, and optimization.
- Includes topics like probability, Fourier series, wavelets, and polynomial approximation.
- Connects algorithm analysis, optimization, probability, statistics, machine learning, and control theory.
- Exercises and examples reinforce concepts for technical proficiency.
- Geared towards advanced undergraduate and beginning graduate students in mathematics, data science, or machine learning.
- When used with lab materials, it enhances both theoretical understanding and practical computation skills.
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