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 Sydney or in NobleProg corporate training centers in Sydney.
NobleProg -- Your Local Training Provider
Sydney King Street
Level 13, 135 King Street, Sydney, Australia, NSW 2000
The business centre in King Street, Sydney is in the energetic heart of Sydney's CBD, surrounded by major financial instituti...
The business centre in King Street, Sydney is in the energetic heart of Sydney's CBD, surrounded by major financial institutions, blue-chip companies and premier retail stores. The premium office building sits south side of King Street between Pitt and Castlereagh Streets, and houses The Glasshouse, a three level retail centre fronting Pitt Street Mall that includes over 27 specialty retail stores. The business centre is located on level 13 and showcases floor to ceiling glass with spectacular views over the CBD and beyond. High-end retail stores on Castlereagh Street, Pitt St Mall and the Queen Victoria Building are all within a few minutes' walk and undercover access takes you directly to Town Hall and Martin Place Train Stations, and major bus routes are right on your doorstep. You'll find a wide choice of lunchtime options nearby, including some of Sydney's best restaurants and cafes, and Sydney's iconic Hyde Park is only a short stroll. It's an address that's perfectly positioned for your business growth in the future.
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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