Анализ данных и машинное обучение

2024/2025

Статус: Маго-лего

Кто читает: Кафедра прикладной математики и информатики (Нижний Новгород)

Когда читается: 2 модуль

Онлайн-часы: 90

Охват аудитории: для своего кампуса

Язык: русский

Кредиты: 6

Полная версия программы учебной дисциплины

Аннотация

The course is devoted to the presentation of modern data analysis and machine learning methods that are widely used in computer vision. The main emphasis is placed on such sections as learning and inference in vision. A taxonomy of models that relate the measured image data and the actual scene content is studied. Generative and discriminative models Classification, regression and clustering methods.

Цель освоения дисциплины

Mastering theoretical background of machine learning.
Obtaining skills of the correct selection of methods for solving the problem

Планируемые результаты обучения

Distinguish the main tasks of machine learning
Process tabular data
• Train and validate linear models for classification and regression problems
• Apply regularization to address overfitting
• Train and validate decision tree models for classification and regression problems
• Distinguish components of learning error
• Train and validate KNN model
• Apply dimensionality reduction to data
• Perform cluster analysis
• Train MLP for supervised learning taks