|Written by Ian Elliot|
|Thursday, 09 March 2017|
Sometimes the news is reported well enough elsewhere and we have little to add other than to bring it to your attention.
No Comment is a format where we present original source information, lightly edited, so that you can decide if you want to follow it up.
(a) cases that are straightforward to migrate (the good parts);
(b) cases that require manual and ad-hoc migration (the bad parts);
(c) cases that cannot be migrated due to limitations and restrictions of ES6 (the ugly parts).
“IMHO the class syntax is misleading, as JS “classes” are not actually classes. Using prototypal patterns seems like a simpler way to do inheritance.” (Developer of system isomer)
It is good to remember that not everyone thinks that class based. object oriented. lanuages are the only solution.
This seems like a really good idea, but why isn' t this the way it is always done? It seems that HTTP based APIs don't really count and we don't consider them real enough to develop tools for.
Our approach also correctly determined whether extracted request data was consistent or inconsistent with the data requirements with a precision of 87.9% for payload data and 99.9% for query data. In a systematic analysis of the inconsistent cases, we found that many of them were due to errors in the client code. The here proposed checker can be integrated with code editors or with continuous integration tools to warn programmers about code containing potentially erroneous requests.
Deep learning is increasingly attracting attention for processing big data. Existing frameworks for deep learning must be set up to specialized computer systems. Gaining sufficient computing resources therefore entails high costs of deployment and maintenance.
You can download the code from: https://github.com/mil-tokyo where you will also find a fast matrix library
Our contributions are the following:
• We implemented the fastest matrix library and deep learning library that can run on web browsers using GPGPU. The source code is provided as open-source software.
• We describe the possibility of training large scale CNN in a distributed manner without installing software in computation nodes, except for a generic plugin.
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|Last Updated ( Thursday, 09 March 2017 )|