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Обычная версия сайта
2023/2024

Методы оптимизации в машинном обучении

Статус: Маго-лего
Когда читается: 1, 2 модуль
Онлайн-часы: 52
Охват аудитории: для своего кампуса
Язык: английский
Кредиты: 6
Контактные часы: 10

Course Syllabus

Abstract

Optimization methods are the basis for solving many problems in computer science. For example, in machine learning, the optimization problem must be solved every time you configure some model of algorithms based on data. Moreover, the practical applicability of the machine learning method itself depends on the effectiveness of solving the corresponding optimization problem. This course is devoted to the study of classical and modern methods for solving continuous optimization problems (including non-convex), as well as the features of using these methods in optimization problems that arise in machine learning. The main emphasis in the materials is on the practical aspects of the implementation and use of methods. By the beginning of the course, students are required to have a basic knowledge of linear algebra. Students’ academic performance is evaluated using programming assignments, theoretical homework and scientific experiments with the final report.