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Total Size:
19.9 MB
Info Hash:
204CD177BD5203868E7CA391B5AB494500C70164
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July 5, 2025, 12:07 p.m.
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(Last updated: July 5, 2025, 12:09 p.m.)
| File | Size |
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| ['Cochard G. Mathematics for Digital Science 3. Data Analysis...Optimization 2025.pdf'] | 0 bytes |
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SOURCE: Cochard G. Mathematics for Digital Science 3. Data Analysis...Optimization 2025
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MEDIAINFO
Textbook in PDF format Over the past century, advancements in computer science have consistently resulted from extensive mathematical work. Even today, innovations in the digital domain continue to be grounded in a strong mathematical foundation. To succeed in this profession, both today's students and tomorrow’s computer engineers need a solid mathematical background. The goal of this book series is to offer a solid foundation of the knowledge essential to working in the digital sector. Across three volumes, it explores fundamental principles, digital information, data analysis, and optimization. Whether the reader is pursuing initial training or looking to deepen their expertise, the Mathematics for Digital Science series revisits familiar concepts, helping them refresh and expand their knowledge while also introducing equally essential, newer topics. Preface Linear Modeling for Two-Dimensional Data Multidimensional Data Analysis Introduction to Automatic Classification Linear Programming Elements of Graph Theory Path Optimization Transportation Problems Scheduling Problems References List of Authors Index
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