The Landscape of Modern Machine Learning: A Review of Machine,
  Distributed and Federated Learning
Omer Subasi Oceane Bel Joseph Manzano Kevin Barker
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.