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 Burnaby or in NobleProg corporate training centers in Burnaby.
NobleProg -- Your Local Training Provider
Burnaby - Metrotown
Suite 2600, 4720 Kingsway, Burnaby, Canada, V5H 4N2
The Burnaby Metrotown Centre is a 30-storey office building which is centrally located by Metrotown Sky train station and con...
The Burnaby Metrotown Centre is a 30-storey office building which is centrally located by Metrotown Sky train station and connected to the Metropolis shopping mall in Burnaby.
Burnaby Centre
Suite 200, 4170 Still Creek Drive , Burnaby , Canada, V5C 6C6
The Burnaby Centre is in a premier business park in North Burnaby. It is located close to Highway 1 and within walking distan...
The Burnaby Centre is in a premier business park in North Burnaby. It is located close to Highway 1 and within walking distance of Brentwood Town Centre and Gilmore SkyTrain Station.
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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