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. Wellington onsite live Apache SINGA trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Wellington, Plimmer Towers
Level 31, 2-6 Gilmer Terrace, Wellington, new zealand, 6011
Located in the heart of Wellington’s CBD, Plimmer Towers is in one of Wellington’s most desirable locations; situated in ...
Located in the heart of Wellington’s CBD, Plimmer Towers is in one of Wellington’s most desirable locations; situated in the north-east of Gilmer Terrace and Boulcott Street, down Plimmer Step. With a short walk to Lambton Quay and immediate vehicle access to the Terrace and motorways and being well serviced by public transport, it’s hard to find a better positioned office, with an impressive street perspective, and panoramic views over Wellington and harbour. Overlooking the waterfront and the Golden Mile, the centre is a pivotal hub surrounded by some of the best cafés, restaurants and bars, and offering access to the premier retail strip and links to Boulcott Street. The shopping precincts; Chew’s Lane, Old Bank Arcade and Kirkcaldie & Stains are all a short walk away. Plimmer Towers includes retail, a 4 Star Travelodge Hotel, and multi-level car parking with 24/7 access. Plimmer Towers is classified as a low earthquake risk under NZSEE Rating and includes sustainable features such as energy efficient lighting and intelligent lighting controls. Centre occupants reap the benefits of first-class on-site facilities and amenities including meeting rooms, business lounge, onsite bike racks, shower and bathroom facilities, and secure lockers.
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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