Practical Statistical Learning and Data Science Methods: Case Studies from LISA 2020 Global Network, USA by O. Olawale Awe, Eric A. Vance ISBN 9783031722158, 9783031722141, 3031722159, 3031722140, 2520-193X, 2520-1948 instant download

Practical Statistical Learning and Data Science Methods: Case Studies from LISA 2020 Global Network, USA by O. Olawale Awe, Eric A. Vance ISBN 9783031722158, 9783031722141, 3031722159, 3031722140, 2520-193X, 2520-1948 instant download

DOI: 10.1007/978-3-031-72215-8 — 
This collective volume offers practical strategies for implementing machine learning and data science techniques, with fully peer-reviewed articles that reflect the knowledge and experiences gained within the global LISA 2020 network. Through a series of compelling case studies, readers delve into practical methodologies, real-world applications, and innovative approaches in machine learning and data science. Topics covered in this volume span a wide range of applications, including machine learning in healthcare data analysis, deep learning models for rainfall modeling, techniques for interpreting machine learning models in BMI classification for obesity studies, and a comparative analysis of sampling methods in machine learning applications in healthcare. By addressing the evolving data analytics landscape in multiple ways, this volume is a valuable resource for practitioners, researchers, and students. The LISA 2020 Global Network is dedicated to building statistical and data science capacity in developing countries through the establishment of collaborative laboratories, also known as “statistical labs.” These statistical labs function as engines of development, nurturing the next generation of collaborative statisticians and data scientists while providing essential research infrastructure for researchers, data producers, and policymakers.