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 Oxford or in NobleProg corporate training centers in Oxford. 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 Oxford. The top-quality Oxford Business Park Centre is located in a modern building in Oxford's premier business district, just inside the ring road and a 40 minute drive from London. The park offers a thriving environment for businesses of all sizes, working in a range of sectors including engineering, electronics, telecommunications and government agencies. Over 45 local and international companies and about 4,000 people are based here and a number have chosen this as the location for their... Read more
Introduction to Deep Learning
Neural Networks Fundamentals using TensorFlow as Example
the subject. it seemed interesting, but I left knowing not much more than before.
Introduction to Deep Learning
way of conducting and example given by the trainer
ORANGE POLSKA S.A.
Machine Learning and Deep Learning
sposób prowadzenia i przykładay podawane przez trenera
Communication with lecturers
Artificial Neural Networks, Machine Learning, Deep Thinking
Possibility to discuss the proposed issues yourself
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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