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. Melbourne onsite live Apache SINGA trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
385 Bourke Street is located in the bustling Central Business District (CBD) and retail precinct of Melbourne's commercial hu...
385 Bourke Street is located in the bustling Central Business District (CBD) and retail precinct of Melbourne's commercial hub, making it by far the most sought after address in the City. Positioned directly opposite the Bourke street Mall, the 41 level tower houses a two level retail complex, known as the Galleria Retail Centre. Showcased underneath an impressive high glass ceiling, the retail specialty stores offer the best in giftware, fashion, food and services. The premium grade property is uniquely positioned on a 45 degree angle to the Melbourne CBD grid, providing excellent 360 degree views and has excellent access to public transport, with trams running along both Bourke and Elizabeth Streets and train and bus stations within 500 metres.
Cliftons Perth
Parmelia House, 191 St Georges Terrace, Perth, Australia, 6000
Located within the historic Bishops See precinct, it sits at the western end of Perth’s Commercial Business District
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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