The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning
This is an incremental review paper that synthesizes existing knowledge for newcomers to machine learning.
The paper provides a high-level review of modern machine learning, covering advanced algorithms, applications, and frameworks, including parallel distributed learning, deep learning, and federated learning, to serve as an introductory text for the field.
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.