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 trainings in Hamburg can be carried out locally on customer premises or in NobleProg corporate training centers.
Our training facilities are located in the Betahaus at Eifflerstraße 43 in Hamburg. E...
Overview
Our training facilities are located in the Betahaus at Eifflerstraße 43 in Hamburg. Easily accessible and centrally located in the Hanseatic city steeped in tradition, this is the ideal location for our participants.
Arrival
The NobleProg training facilities are located in the middle of the Schanzenviertel. The nearest bus stops are "Schulterblatt" for Metrobus line 15 and "Sternbrücke" for Metrobus line 3. The nearest S-Bahn and U-Bahn stations are Sternschanze.
Parking
In the area along the Eifflerstrasse and the nearby side streets, cars can be parked, even if you have to search for a moment. There is no charge for parking..
Local Services
The Schanzenviertel offers a wide range of gastronomic options and with Pyjama Park, Hotel Boston and other small and medium-sized hotels, local accommodation is also possible.
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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Testimonials (2)
We had an overview about Machine Learning, Neural Networks, AI with practical examples.
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