ANALYSIS OF GRADIENT DECREASE ALGORITHMS

Авторы

  • Alimardonov Shokhrukh Erkin o‘g‘li

Ключевые слова:

Gradient descent, Batch gradient, Stochastic gradient descent, Mini-Batch gradient descent.

Аннотация

This paper presents a comprehensive comparison of three gradient descent algorithms commonly used in machine learning and deep learning: Batch gradient descent, stochastic gradient descent, and mini-batch gradient descent. Differences between these algorithms in terms of gradient descent computational efficiency, stability, and learning dynamics are explained. Provides a clear and concise overview of each algorithm, their advantages and disadvantages, making it easy to understand their suitability for a specific problem and data set. Relevant information is provided to illustrate the difference between these algorithms.

Библиографические ссылки

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https://www.baeldung.com/cs/gradient-stochastic-and-mini-batch

Загрузки

Опубликован

2024-03-04