Сучасні методи та моделі машинного і глибокого навчання з параметрами

Abstract

This work explores contemporary methods and models in machine and deep learning with parameters. The study encompasses a comprehensive review of parameterized models, their applications, and the impact of varying parameters on model performance. The study encompasses a comprehensive review of parameterized models, their applications, and the impact of varying parameters on model performance. Additionally, the paper investigates the latest trends and innovations in the rapidly evolving landscape of machine and deep learning, providing insights into the optimization and enhancement of model capabilities through parameter tuning.