Название: Machine Learning for Intelligent Decision Science Автор: Jitendra Kumar Rout, Minakhi Rout
Издательство: Springer
Серия: Algorithms for Intelligent Systems
Год: 2020
Страниц: 219
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty. Featuring contributions from data scientists, practitioners and educators, the book covers a range of topics relating to intelligent systems for decision science, and examines recent innovations, trends, and practical challenges in the field. The book is a valuable resource for academics, students, researchers and professionals wanting to gain insights into decision-making.
Machine Learning (ML) is the study of algorithms and mathematical models that computer systems use to progressively improve their performance on a specific task. Machine learning-based decision-making model develops new, intelligent, hybrid, and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty. Machine learning is widely used in various domains to perform various tasks effectively to analyze and process huge amount of data for predictive analytics, recommendations, classification, clustering, feature learning, dimensionality reduction, pattern recognition, and information retrieval in less amount of time with greater accuracy.
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