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 Edinburgh can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Edinburgh
83 Princes Street , Edinburgh, united kingdom, EH2 2ER
The training rooms is located under a 10 minute walk from Edinburgh Rail Station
This centre's location on Edinburg...
The training rooms is located under a 10 minute walk from Edinburgh Rail Station
This centre's location on Edinburgh's world-famous Princes Street takes some beating. Right in the centre of Scotland's capital city, these prestigious business premises are spread across six floors with fantastic views over Princes Street Gardens towards the Royal Mile and Edinburgh Castle. As well as having all the usual amenities of a major city on its doorstep, the building also has a car park. Prosperous Edinburgh is a global centre for business, science, education and the arts and is said to have the strongest economy of any UK city outside London. Banking has been a part of the economic life of Edinburgh for over 300 years and today it is the UK's second financial centre after London and Europe's fourth by equity assets. Tourism, financial services and banking are particularly important employers as well as education, the public sector and hi-tech research and development.
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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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