Practical Statistical Learning and Data Science Methods: Case Studies from Lisa 2020 Global Network, USA
暫譯: 實用統計學習與數據科學方法：來自Lisa 2020全球網絡的案例研究，USA

Awe, O. Olawale, Vance, Eric

Practical Statistical Learning and Data Science Methods: Case Studies from Lisa 2020 Global Network, USA
  • 出版商: Springer
  • 出版日期: 2025-02-05
  • 售價: $9,760
  • 貴賓價: 9.5 折 $9,272
  • 語言: 英文
  • 頁數: 756
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031722140
  • ISBN-13: 9783031722141
  • 相關分類: Data Science

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

This contributed volume offers practical implementation strategies for statistical learning and data science techniques, with fully peer-reviewed papers that embody insights and experiences gathered within the LISA 2020 Global Network. Through a series of compelling case studies, readers are immersed in practical methodologies, real-world applications, and innovative approaches in statistical learning and data science.

Topics covered in this volume span a wide array of applications, including machine learning in health data analysis, deep learning models for precipitation modeling, interpretation techniques for machine learning models in BMI classification for obesity studies, as well as a comparative analysis of sampling methods in machine learning health applications. By addressing the evolving landscape of data analytics in many ways, this volume serves as a valuable resource for practitioners, researchers, and students alike.

The LISA 2020 Global Network is dedicated to enhancing statistical and data science capabilities in developing countries through the establishment of collaboration laboratories, also known as "stat labs." These stat labs function as engines for development, nurturing the next generation of collaborative statisticians and data scientists while providing essential research infrastructure for researchers, data producers, and decision-makers.

商品描述(中文翻譯)

這本貢獻集提供了統計學習和數據科學技術的實用實施策略，包含經過全面同行評審的論文，體現了在 LISA 2020 全球網絡中收集的見解和經驗。透過一系列引人入勝的案例研究，讀者將沉浸於統計學習和數據科學中的實用方法論、現實應用和創新方法。

本卷涵蓋的主題涉及廣泛的應用，包括健康數據分析中的機器學習、降水建模的深度學習模型、用於肥胖研究的身體質量指數（BMI）分類的機器學習模型解釋技術，以及機器學習健康應用中的抽樣方法比較分析。這本書以多種方式應對數據分析不斷演變的格局，對於從業者、研究人員和學生來說，都是一個寶貴的資源。

LISA 2020 全球網絡致力於通過建立合作實驗室（也稱為「統計實驗室」）來增強發展中國家的統計和數據科學能力。這些統計實驗室作為發展的引擎，培養下一代的合作統計學家和數據科學家，同時為研究人員、數據生產者和決策者提供必要的研究基礎設施。

作者簡介

O. Olawale Awe holds a PhD in Statistics from the University of Ibadan, Nigeria, and an MBA from Obafemi Awolowo University, Ile-Ife, Nigeria. He currently serves as the Vice President of the International Association for Statistics Education (IASE). His affiliations include being an Elected Council Member of the International Statistics Institute (ISI), Vice President of Global Statistical Engagements of the LISA 2020 Global Network, USA, and a research professor and machine learning team leader at the Statistical Learning Laboratory (SaLLy) of the Federal University of Bahia, Brazil. He has published more than 100 research papers in international and national journals and conferences, and he has also published five books and monographs. As the pioneering LISA Fellow of the LISA 2020 Global Network at the University of Colorado, Boulder, USA, he has significantly contributed to the global statistical community.

Eric A. Vance is an Associate Professor of Applied Mathematics and the Director of the Laboratory for Interdisciplinary Statistical Analysis (LISA) at the University of Colorado Boulder, USA. He is the Director of the LISA 2020 Global Network. He is an Elected Member of the ISI and a Fellow of the American Statistical Association (ASA). Dr. Vance researches what individual statisticians and data scientists need to know to become effective interdisciplinary collaborators and what institutions can do to promote interdisciplinary collaboration to make data-driven decisions. He was the 2023 winner of the ASA's W.J. Dixon Award for Excellence in Statistical Consulting.

作者簡介(中文翻譯)

O. Olawale Awe 擁有尼日利亞伊巴丹大學的統計學博士學位，以及尼日利亞伊萊伊費的奧巴費米·阿沃洛沃大學的工商管理碩士學位。他目前擔任國際統計教育協會（IASE）的副會長。他的職位包括國際統計學會（ISI）當選理事會成員、LISA 2020 全球網絡的全球統計參與副會長（美國），以及巴西巴伊亞聯邦大學統計學習實驗室（SaLLy）的研究教授和機器學習團隊負責人。他在國際和國內期刊及會議上發表了超過100篇研究論文，並出版了五本書籍和專著。作為美國科羅拉多大學博爾德分校LISA 2020全球網絡的首位LISA研究員，他對全球統計社群做出了重要貢獻。

Eric A. Vance 是美國科羅拉多大學博爾德分校應用數學的副教授及跨學科統計分析實驗室（LISA）的主任。他是LISA 2020全球網絡的主任。他是國際統計學會（ISI）的當選成員，也是美國統計協會（ASA）的研究員。Vance博士的研究重點在於個別統計學家和數據科學家需要了解的知識，以成為有效的跨學科合作夥伴，以及機構可以採取哪些措施來促進跨學科合作，以便做出基於數據的決策。他是2023年美國統計協會W.J. Dixon卓越統計諮詢獎的得主。

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