The book aims to address the weaknesses in Multi-Criteria Decision-Making (MCDM) methods and enhance the accuracy and effectiveness of MCDM methods in selecting the best alternatives in various fields. It applies traditional methods and proposes modified methods to human development index data and presents Python code examples.
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Semra Erpolat Tasabat completed her education in Statistics, earning her Ph.D. from Mimar Sinan Fine Arts University and Marmara University. She has been a full-time lecturer at Mimar Sinan Fine Arts University. Dr. Tas,abat has made significant contributions to the field of statistics and decision methods, and her expertise is evident through her academic appointments and research activities.
Tug˘ba Kıral Ozkan is a full-time lecturer at Bahces,ehir University. She received her Ph.D. in Operations Research from Marmara University, Institute of Social Sciences. Her research interests include measurement and evaluation, optimization methods, and multi-criteria decision-making. She has published scientific journals and conference papers on optimization, multi-criteria decision-making, social network analysis, statistical data analysis, and machine learning. She offers research methods and statistical data analysis courses in undergraduate and graduate programs at BAU.
Olgun Aydın holds a Ph.D. and is an expert in the field of deep learning, statistics, and machine learning. He works as an Assistant Professor at Gdansk University of Technology in Poland. Dr. Aydin is the author and co-author of several R packages. He is passionate about sharing his expertise in data science and is actively involved in the Why R? Foundation and the Polish Artificial Intelligence Society.
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