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 trainings in Brisbane can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
200 Mary Street, Brisbane
Level 16, 200 Mary Street, Brisbane, Australia, 4000
The 200 Mary Street business centre is located only 125 metres from the Brisbane GPO, strategically located within Brisbaneâ€...
The 200 Mary Street business centre is located only 125 metres from the Brisbane GPO, strategically located within Brisbane’s premier financial district known as ‘the Golden Triangle’. Situated on Level 16 and boasting views over the Brisbane River, hinterland and the CBD, the centre provides the ideal setting to showcase your business in a contemporary environment with fully-equipped work space.
200 Mary Street is immersed in Brisbane’s city life with everything at your doorstep, from key transport links to restaurants and bar as well as hotels. The centre is serviced by the City Cat service and Central Train Station, which is less than five minutes walk.
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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