Online or onsite, instructor-led live Apache SINGA training courses demonstrate through interactive discussion and hands-on practice the fundamentals and advanced topics of Apache SINGA.
Apache SINGA 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 Apache SINGA training can be carried out locally on customer premises in Montpellier or in NobleProg corporate training centers in Montpellier.
NobleProg -- Your Local Training Provider
Montpellier, Garosud
NobleProg Montpellier, 48, rue Claude Balbastre, Montpellier, france, 34070
– Access Tram stop Victoire 2 Line 2 direction Saint Jean de Védas.
-Tram access then Bus take tram line 2 Sabine stop to...
– Access Tram stop Victoire 2 Line 2 direction Saint Jean de Védas.
-Tram access then Bus take tram line 2 Sabine stop towards Saint Jean de Védas then the “La Ronde” bus stop Patrice Lumumba.
- Access by car from the A9 exit 31 “Saint Jean de Védas” Montpellier Ouest, silver cross MOSSON.
-Access by train from Saint Roch station, Tram line 2 towards Saint Jean de Védas, Victory 2 stop.
– Access by plane from Montpellier airport 10 minutes by car, exit 31 of the A9 towards Barcelona or by bus from the airport line 120 to Place de l'Europe then Tram line 2 towards Saint Jean de Védas stop Victory 2
SINGA is a general distributed deep learning platform for training big deep learning models over large datasets. It is designed with an intuitive programming model based on the layer abstraction. A variety of popular deep learning models are supported, namely feed-forward models including convolutional neural networks (CNN), energy models like restricted Boltzmann machine (RBM), and recurrent neural networks (RNN). Many built-in layers are provided for users. SINGA architecture is sufficiently flexible to run synchronous, asynchronous and hybrid training frameworks. SINGA also supports different neural net partitioning schemes to parallelize the training of large models, namely partitioning on batch dimension, feature dimension or hybrid partitioning.
Audience
This course is directed at researchers, engineers and developers seeking to utilize Apache SINGA as a deep learning framework.
After completing this course, delegates will:
understand SINGA’s structure and deployment mechanisms
be able to carry out installation / production environment / architecture tasks and configuration
be able to assess code quality, perform debugging, monitoring
be able to implement advanced production like training models, embedding terms, building graphs and logging
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