Online or onsite, instructor-led live Chainer training courses demonstrate through interactive hands-on practice how to use Chainer to build and train neural networks in Python while making the code easy to debug.
Chainer 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. Transylvania onsite live Chainer trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Brasov, Calea Bucuresti Street
NobleProg Brasov, 13 Calea Bucuresti Street Sacele, Brasov, romania, 505600
The hotel is situated at the city entrance, being the best conference and training location in Brasov. Three conference rooms can accommodate up to 170 guests and can be modified for the company needs. These training rooms are equipped with the all necessities of a good conference or training.
Salile de training sunt situate central în Sibiu, pe principalul bulevard. Clădirea hotelului care le gazduieste este de factură clasicistă si reprezinta un punct de referinta arhitecturala a orasului.
Turnul Sfatului, Galeria de Arta Contemporana, sau parcurile Corneliu Coposu si Astra se află în imediata apropiere.
Pentru a ajunge aici de la gara, puteti merge pe jos 20min sau cu autobuzul 5 circa 10min
Locuri de parcare găsiți în parcarea supravegheata, sau pe străzile alăturate.
Cluj-Napoca, Pitești Street
NobleProg Cluj-Napoca, Strada Pitești 19, Cluj-Napoca, romania, 400124
ClujHUB has more rooms for events and training sessions, which can host from 4 to 80 people. These areas can be setup up to fit the companies need. The location is great, 10 minutes walk from the historical city center.
This instructor-led, live training in Transylvania (online or onsite) is aimed at researchers and developers who wish to use Chainer to build and train neural networks in Python while making the code easy to debug.
By the end of this training, participants will be able to:
Set up the necessary development environment to start developing neural network models.
Define and implement neural network models using a comprehensible source code.
Execute examples and modify existing algorithms to optimize deep learning training models while leveraging GPUs for high performance.
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