Collaborative Machine Learning: Evolving Workflows

This chapter explores the significance of collaboration in distributed machine learning training, emphasizing how centralized systems can enhance communication among researchers. It covers the integration of collaboration tools, practical features, and the importance of sharing experimental results within the evolving landscape of machine learning workflows. The discussion also highlights user experiences with prominent frameworks and the challenges of adapting to rapidly changing tools in the industry.