Online or onsite, instructor-led live Horovod training courses demonstrate through interactive hands-on practice how to use Horovod to run distributed deep learning trainings and scale it up to run across multiple GPUs in parallel.
Horovod training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Horovod training can be carried out locally on customer premises in Recife or in NobleProg corporate training centers in Recife.
NobleProg -- Your Local Training Provider
Recife - JCPM Trade Center
60 Eng. Antonio de Goes Avenue, 7º and 14º floor, , Recife, Brazil, 51010-000
The Recife JCPM Trade Center is in a 20-story building. The center has access to a helipad and five floors of parking. It is 10km from Guararapas International Airport.
Recife-Cicero Dias Shopping Center Recife
Rua Padre Carapuceiro, 858 , Recife, Brazil, 51020-280
The business center is located in the Cicero Dias Tower, part of a prestigious complex of five buildings, the Queiroz Galvão Center. Its stands out for its distinctive architecture and for being located in an area with a consolidated entrepreneurial vocation. The business center has a privileged position in Pernambuco, in one of the greatest development axis of northeastern Brazil. The business center is walking distance to one of the Recife's greatest shopping centers and from Shopping subway station. It is also 30 minutes away from the Port of Suape, one of the most important seaports in the country and a 7-minute drive from Guararapes International Airport.
This instructor-led, live training in Recife (online or onsite) is aimed at developers or data scientists who wish to use Horovod to run distributed deep learning trainings and scale it up to run across multiple GPUs in parallel.
By the end of this training, participants will be able to:
Set up the necessary development environment to start running deep learning trainings.
Install and configure Horovod to train models with TensorFlow, Keras, PyTorch, and Apache MXNet.
Scale deep learning training with Horovod to run on multiple GPUs.
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