A Practical Guide to Optimization in Engineering and Data Science

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Éditeur :

Springer

Paru le : 2026-01-08

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 engineerin...
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Éditeur

Collection
n.c

Parution
2026-01-08

Pages
325 pages

EAN papier
9783032046321

Wellington Rodrigo Monteiro received his Ph.D. in Industrial and Systems Engineering from the Pontifical Catholic University of Parana (PUCPR), Brazil, a Master’s in Industrial and Systems Engineering from PUCPR, and a Bachelor’s in Computer Engineering from PUCPR. He has over ten years of experience working as a data scientist in large international corporations and startups. He works as a lead machine learning engineer at Nubank and as an assistant professor at PUCPR. His interests are rooted in machine learning, evolutionary algorithms, and multi-objective optimization applications in the industry. Gilberto Reynoso Meza received his Ph.D. in Automation from the Universitat Politècnica de València (Spain) and his B.Sc. (2001) in Mechanical Engineering from the Tecnológico de Monterrey, Campus Querétaro (Mexico). Currently, he is with the Industrial and Systems Engineering Graduate Program (PPGEPS) of the Pontifical Catholic University of Parana (PUCPR), Brazil, as an associate Professor. His main research interests are computational intelligence methods for control engineering, multi-objective optimization, many-objectives optimization, multi-criteria decision-making, evolutionary algorithms, and machine learning.

Caractéristiques détaillées - droits

EAN PDF
9783032046338
Prix
158,24 €
Nombre pages copiables
3
Nombre pages imprimables
32
Taille du fichier
14561 Ko
EAN EPUB
9783032046338
Prix
158,24 €
Nombre pages copiables
3
Nombre pages imprimables
32
Taille du fichier
81480 Ko

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