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A Practical Guide to Optimization in Engineering and Data Science - Gilberto Reynoso Meza,Wellington Rodrigo Monteiro

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2026-01-09
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This book offers a hands-on and comprehensive guide to optimization techniques tailored for data scientists and engineers, combining theoretical foundations with practical applications. It begins by demystifying core concepts and types of optimization, then explores their relevance across engineering and data science domains. Readers are introduced to essential mathematical tools, single- and multi-objectiv ... Visas aprašymas

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This book offers a hands-on and comprehensive guide to optimization techniques tailored for data scientists and engineers, combining theoretical foundations with practical applications. It begins by demystifying core concepts and types of optimization, then explores their relevance across engineering and data science domains. Readers are introduced to essential mathematical tools, single- and multi-objective optimization methods, and a wide range of algorithms including gradient-based techniques, evolutionary strategies, and swarm intelligence. The book also lists real-world applications across industries and provides several Python-based examples, enabling readers to implement and experiment with optimization models in practice. With its structured approach and rich set of examples, this book serves as a valuable resource for professionals and researchers seeking to apply optimization effectively in their work.

Daugiau informacijos

Autorius Gilberto Reynoso Meza, Wellington Rodrigo Monteiro
Leidėjas Springer-Verlag GmbH
Išleidimo metai 2026
Viršelio tipas Kieti viršeliai
EAN 9783032046321
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185,61 € 247,48 €