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Scientific Computing: An Introductory Survey, Revised Second Edition
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Scientific Computing presents a broad overview of methods and software for solving mathematical problems arising in computational modeling and data analysis.
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- A broad overview of methods and software for solving mathematical problems in computational modeling and data analysis.
- Focuses on the motivation and ideas behind the algorithms rather than detailed analysis.
- Proper problem formulation, effective solution algorithm selection, and result interpretation emphasized.
- Includes pointers to Python software and the Chebfun package.
- Expansions on barycentric formulation, Lagrange polynomial interpretation, and stochastic methods.
- Available interactive educational modules illustrate concepts and algorithms.
| Publisher | SIAM - Society for Industrial and Applied Mathematics |
| Publication date | November 14, 2018 |
| Edition | Second |
| Language | English |
| Print length | 567 pages |
| ISBN-10 | 1611975573 |
| ISBN-13 | 978-1611975574 |
| Item Weight | 2.61 pounds (1.18 kg) |
| Dimensions | 9.65 x 1.3 x 7.72 inches (24.5 x 3.3 x 19.6 cm) |
Who Should Buy?
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Students in STEM
Ideal for undergraduate and graduate students seeking foundational knowledge in scientific computing methodologies and applications.
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Professionals in Research
Beneficial for researchers needing to understand computational techniques for modeling and solving scientific problems.
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Educators in Computing
Valuable for educators looking for resources to teach scientific computing concepts effectively in classroom settings.
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Casual Learners
Not suitable for individuals seeking quick, informal learning resources without in-depth technical detail.
Product Description
Scientific Computing: An Introductory Survey, Revised Second Edition
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Pros
- Comprehensive coverage of topics
- Clear and concise explanations
- Well-structured for beginners
- Up-to-date with new technologies
- Numerous practical examples
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Features & Benefits
- Focuses on motivation and ideas behind the algorithms presented
- Broad overview of methods and software for mathematical problem-solving
- Both for a textbook and reference
- Updated version now includes pointers to Python software
- Ideal for computationally oriented disciplines
- Includes over 100 interactive educational modules
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