Data Scientists (& ML Engineers) save between 5-10 hours/week on average by working on Deque

Deque makes distributed training very simple to use and can speed up training at infinite scalability with single click abstraction saving hours of platform work - no cluster setup or administration required. From notebook and job optimizations to OS tweaks, training workloads run faster on Deque

By using the cloud resources optimally (within seconds) and using on-prem infrastructure transparently, clients can achieve. Deque can lower cloud bills associated with deep learning by over 20% [no surcharge tied to consumption and through optimal utilization.

Deque’s platform needs ZERO overhead and management to run the training workloads, obviating expenses associated with large platform teams.