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Название: Distributed Machine Learning and Gradient Optimization
Автор: Jiawei Jiang, Bin Cui, Ce Zhang
Издательство: Springer
Год: 2022
Формат: True PDF
Страниц: 179
Размер: 10 Mb
Язык: English
This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods. In the big data era, large-scale datasets pose enormous challenges for the existing machine learning systems. As such, implementing machine learning algorithms in a distributed environment has become a key technology, and recent research has shown gradient-based iterative optimization to be an effective solution.
Автор: Jiawei Jiang, Bin Cui, Ce Zhang
Издательство: Springer
Год: 2022
Формат: True PDF
Страниц: 179
Размер: 10 Mb
Язык: English
This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods. In the big data era, large-scale datasets pose enormous challenges for the existing machine learning systems. As such, implementing machine learning algorithms in a distributed environment has become a key technology, and recent research has shown gradient-based iterative optimization to be an effective solution.