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. Namur onsite live Apache SINGA trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Namur, Hotel de Ville
NobleProg Namur, Rue de Fer, 48 , Namur, Belgium, 5000
Namur is a French-speaking city in Belgium, capital of Wallonia since 1986, and capital of the province of Namur. Occupied...
Namur is a French-speaking city in Belgium, capital of Wallonia since 1986, and capital of the province of Namur. Occupied since the Neolithic period, the confluence of the Sambre and the Meuse saw the birth of the Roman city at the beginning of our era. Former stronghold of the Counts of Namur, attached to the house of Luxembourg and then to the Habsburg Empire, the citadel of Namur was the focus of many sieges over the years. Despite the damage suffered by the conflicts, the city retains a rich movable and immovable heritage. Today the regional capital, the city is the seat of the Parliament of Wallonia, the Walloon Government and the Public Service of Wallonia, but also the host city of the International Francophone Film Festival, the fairground arts festival Namur in May, the Festival Verdur Rock.
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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