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 Liverpool or in NobleProg corporate training centers in Liverpool.
NobleProg -- Your Local Training Provider
Liverpool
Horton House, Liverpool, united kingdom, L2 3PF
This business centre is situated in Exchange Flags, a beautifully restored landmark property at the heart of Liverpool's r...
This business centre is situated in Exchange Flags, a beautifully restored landmark property at the heart of Liverpool's rejuvenated business district. This is Liverpool's best office address. The elegance of the original architecture has been matched by a sympathetic yet stylish refurbishment, which has set a benchmark for Grade A office accommodation across the city. Two office buildings flank an impressive bustling open square, which is enclosed by Liverpool Town Hall. Occupiers so far include legal, accountancy, consulting and property firms and The Ministry of Defence. The World Heritage waterfront, a 10,000-seater arena and a conference centre are on the doorstep as well as the Liverpool One shopping and leisure complex. Not since its days as the foremost port in the world has Liverpool witnessed development activity at current levels. This is a city that means business and is attracting investment and visitors from across the world.
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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