Магистратура
2024/2025
Рекомендательные системы
Статус:
Курс по выбору (Науки о данных (Data Science))
Направление:
01.04.02. Прикладная математика и информатика
Где читается:
Факультет компьютерных наук
Когда читается:
2-й курс, 1, 2 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для всех кампусов НИУ ВШЭ
Преподаватели:
Игнатов Дмитрий Игоревич
Прогр. обучения:
Науки о данных
Язык:
английский
Кредиты:
6
Course Syllabus
Abstract
In this course, we will introduce the problem of building a recommender system (RS) and its relation to other domains of machine learning and information retrieval. We will start by providing an overview of classical approaches for constructing RSs, including content-based and collaborative filtering via matrix factorization. Additionally, we will discuss the metrics and validation schemes commonly employed in RS development.Moving forward, we will delve into modern neural architectures specifically designed for recommender systems. Furthermore, we will explore various techniques frequently utilized in the industry, such as session-based recommender systems, two-stage RSs, and online RSs. Lastly, we may touch upon additional topics of common interest.