Local, 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 "onsite live training" or "remote live training". Onsite live training can be carried out locally on customer premises in Bristol or in NobleProg corporate training centers in Bristol. Remote live training is carried out by way of an interactive, remote desktop.
NobleProg -- Your Local Training Provider
Learn Apache SINGA in our training center in Bristol.
The training rooms are located under a 2 minute walk from Bristol Temple Meads Railway station. From the main exit at Temple Meads Railway Station City Point is directly in front (approx 200 metres). On arrival in main reception a receptionist will direct you to the correct training room. If travelling by car there is a public car park at the rear of the building.
So make the most of your visit to Bristol while enjoying your NobleProg training course. Bristol is a...
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.
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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