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Manifold Learning
Publicado 2024“...The book gives access to python libraries available on gitlab.com, which have been developed as part of the research program [FUI-25] MORDICUS funded by the French government. ...”
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Optimization Problems in Transportation and Logistics: A Practical Guide
Publicado 2024Ligazón do recurso
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Advanced Technologies in Agricultural Engineering and Energy Optimization
Publicado 2024Ligazón do recurso
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Beginners in Computer Science Studies
Publicado 2024“...This paper introduces key concepts and tools that form the core of computer science, starting with an overview of computational thinking, problem-solving, and programming. ...”
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Tecnología de la programación
Publicado 2025“...This book addresses the foundations of modern programming, with a widely used and demanded programming language in scientific disciplines (Python) so that students in mathematics (or other areas) can have a versatile profile when facing problems of problemsdifferent mathematical nature. ...”
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Programming Foundations
Publicado 2025“...Through hands-on learning, each chapter builds both confidence and competence, guiding students from simple scripts to more complex code. By the end of the book, students will not only understand Python’s core principles but also have the skills and tools to tackle real coding challenges within their scientific disciplines....”
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The 1090 Megahertz Riddle
Publicado 2025“...Throughout these chapters, examples and sample Python code are used extensively to explain and demonstrate the decoding process. ...”
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Sensitivity Analysis for Business, Technology, and Policymaking
Publicado 2025“...To facilitate as widespread adoption and penetration of SimDec as possible, all supporting computer codes are available, open-source, in Python, Julia, R, and Matlab. The innovative material will be of primary benefit to practitioners and researchers analyzing data from the social sciences, business, science, engineering, mathematics, and computing. ...”
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The Computational Content Analyst
Publicado 2025“...This book offers practical guidance and Python code to traverse the vast expanses of data—significantly enhancing productivity without compromising scholarly integrity. ...”
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