The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning

Omer Subasi, Oceane Bel, Joseph Manzano, Kevin Barker
12/5/2023
cs.LGcs.AIcs.DC

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Abstract

With the advance of the powerful heterogeneous, parallel and distributed computing systems and ever increasing immense amount of data, machine learning has become an indispensable part of cutting-edge technology, scientific research and consumer products. In this study, we present a review of modern machine and deep learning. We provide a high-level overview for the latest advanced machine learning algorithms, applications, and frameworks. Our discussion encompasses parallel distributed learning, deep learning as well as federated learning. As a result, our work serves as an introductory text to the vast field of modern machine learning.

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@article{subasi2023landscape,
  title  = {The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning},
  author = {Omer Subasi and Oceane Bel and Joseph Manzano and Kevin Barker},
  year   = {2023},
  eprint = {2312.03120},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2312.03120v1}
}

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