A Practical Guide to Optimization in Engineering and Data Science
暫譯: 工程與數據科學中的優化實用指南
Monteiro, Wellington Rodrigo, Meza, Gilberto Reynoso
相關主題
商品描述
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.
商品描述(中文翻譯)
本書提供了一本針對資料科學家和工程師的實用且全面的優化技術指南，結合了理論基礎與實際應用。書中首先解釋了核心概念和優化類型，接著探討它們在工程和資料科學領域的相關性。讀者將接觸到基本的數學工具、單目標和多目標優化方法，以及包括基於梯度的技術、演化策略和群體智慧在內的各種演算法。本書還列出了各行各業的實際應用，並提供了幾個基於 Python 的範例，使讀者能夠在實踐中實施和實驗優化模型。憑藉其結構化的方法和豐富的範例，本書成為專業人士和研究人員在工作中有效應用優化的寶貴資源。
作者簡介
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.
作者簡介(中文翻譯)
威靈頓·羅德里戈·蒙泰羅（Wellington Rodrigo Monteiro）於巴西巴拉那天主教大學（Pontifical Catholic University of Parana, PUCPR）獲得工業與系統工程博士學位，並在同校獲得工業與系統工程碩士學位及計算機工程學士學位。他在大型國際企業和初創公司擔任數據科學家的工作經驗超過十年。目前，他在Nubank擔任首席機器學習工程師，並在PUCPR擔任助理教授。他的研究興趣集中在機器學習、進化算法以及在工業中的多目標優化應用。
吉爾伯托·雷諾索·梅薩（Gilberto Reynoso Meza）於西班牙瓦倫西亞理工大學（Universitat Politècnica de València）獲得自動化博士學位，並於2001年在墨西哥蒙特雷科技大學（Tecnológico de Monterrey, Campus Querétaro）獲得機械工程學士學位。目前，他在巴西巴拉那天主教大學（PUCPR）的工業與系統工程研究生課程（PPGEPS）擔任副教授。他的主要研究興趣包括控制工程的計算智能方法、多目標優化、多目標優化、多準則決策、進化算法和機器學習。
