Data Science or not Data Science? : Différence entre versions
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TenserFlow : https://www.tensorflow.org/ | TenserFlow : https://www.tensorflow.org/ | ||
Wendelin : http://www.nexedi.com/NXD-Document.Blog.Wendelin.Release.0.4.alpha | Wendelin : http://www.nexedi.com/NXD-Document.Blog.Wendelin.Release.0.4.alpha | ||
| + | Square Predict : http://square-predict.net/ | ||
'''Testbeds we use''' | '''Testbeds we use''' | ||
Version du 30 janvier 2016 à 08:43
Welcome on LIPN Wiki about Big Data
With more and more data produced every day, we need to pay a special attention on the technologies to use in order to be able to analyze large amount of data. Big Data is often characterized by the 4 V for Volume, Variety, Velocity, Veracity that constitute challenges for the required tools.
Machine learning is to extract knowledge from data. In short it's a family of algorithms which transform data into model or description with the aim to predict or categorize data. In this field we use also analytics tools which consist to present informations in a more readable way.
The wiki is related to our experience on the Grid5000 and CIRRUS testbeds for the study of the Software, Platform, Infrastructure and Network layers that push forward the Data Science field according to an experimental scientific method.
General discussions on Systems for Big-Data
Infrastructure, programming models, frameworks
Tools we use
Apache Spark : http://spark.apache.org/ Apache Flink : https://flink.apache.org/ TenserFlow : https://www.tensorflow.org/ Wendelin : http://www.nexedi.com/NXD-Document.Blog.Wendelin.Release.0.4.alpha Square Predict : http://square-predict.net/
Testbeds we use
Grid5000 : https://www.grid5000.fr/mediawiki/index.php/Grid5000:Home Cirrus : http://cirrus.uspc.fr
Apache Spark
General information on Apache Spark How to use Spark on Grid5000
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