Distributed deep learning has emerged as an essential approach for training large-scale deep neural networks by utilising multiple computational nodes. This methodology partitions the workload either ...
In this video from the European R Users Meeting, Henrik Bengtsson from the University of California San Francisco presents: A Future for R: Parallel and Distributed Processing in R for Everyone. The ...
Results that may be inaccessible to you are currently showing.
Hide inaccessible results
Feedback