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. Sharjah onsite live Apache SINGA trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
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Sharjah Expo Centre
Al Taawun Street, Al Khan, United Arab Emirates, P.O.Box 3222
Located in the United Arab Emirates (UAE), Expo Centre Sharjah naturally commands a strategic position at the heart of the re...
Located in the United Arab Emirates (UAE), Expo Centre Sharjah naturally commands a strategic position at the heart of the region’s business and commercial hub. As a stable and dynamic country, the UAE is an established gateway to the Middle East and beyond into the CIS region, North Africa and the Indian Subcontinent.
This is one of the newest Expo centres in the UAE. Adjacent to the Corniche with convenient connections to the E11, the UAE’s longest road, it’s a strategic location with excellent links to Dubai and the airport. This centre's location is ideal for companies with international clients, and for those that value convenience, accessibility and practicality. Within walking distance, there is an abundance of restaurants and cafes to explore and enjoy outside of work. Close by, you can also find Sharjah Aquarium
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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