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. Onsite live Chainer training can be carried out locally on customer premises in Barcelona or in NobleProg corporate training centers in Barcelona.
NobleProg -- Your Local Training Provider
Barcelona City
NobleProg Barcelona, C/ de Mallorca, 501, Barcelona, spain, 08013
With a population of 1 604 555 inhabitants and constantly growing, Barcelona is the second most populated city of Spain after...
With a population of 1 604 555 inhabitants and constantly growing, Barcelona is the second most populated city of Spain after Madrid, and the eleventh of the European Union. It is located on the shores of the Mediterranean Sea, about 120 km south of the A mountainous chain of the Pyrenees and the border with France and is globally recognized as a global city because of its cultural, financial, commercial and tourist importance.
It has a great service of public transport called TMB formed by diverse lines of railroad, tram, metro and buses that circulate throughout the city.
Located in a magnificent location in "L'Esquerra de l'Eixample", one of the main business centers of Barcelona, with universities, metro, buses, Sants station, post office and all the services you can need a few steps away
This instructor-led, live training in Barcelona (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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