دانلود کتاب یادگیری ماشین برای علوم تصمیم گیری با مطالعات موردی در پایتون

Decision science is a set of quantitative tools for informing individual- and population-level decision-making. It includes decision analysis, cost-effectiveness analysis, constrained optimization, risk analysis, and behavioral decision theory. Decision science provides a unique framework for understanding and designing strategies to address such problems by focusing on decisions as the unit of study. Machine learning generates usable models by evaluating a large number of solutions against the given data and selecting the one that best fits the situation. As a result, machine learning can be useful for solving problems that require a lot of human effort. It can efficiently and accurately inform judgments and generate predictions about challenging topics. Insurers may predict likely results of crucial decisions using the Data Science Life Cycle and Decision Science platform, which is powered by machine learning, to achieve optimal decision outcomes. After decisions have been made, the results can be used to inform future decisions. As a result, high-value decision-making is streamlined and repeatable, which benefits both shareholders and policyholders.