Author(s)

NameInstitutionMail AddressSocial Contacts
Brunella D'AnziINFN Sezione di Bari brunella.d'anzi@cern.chSkype: live:ary.d.anzi_1; Linkedin: brunella-d-anzi
Nicola De FilippisINFN Sezione di Bari nicola.defilippis@ba.infn.itN/A

Domenico Diacono

INFN Sezione di Bari

domenico.diacono@ba.infn.itN/A
Walaa ElmetenaweeINFN Sezione di Bariwalaa.elmetenawee@cern.chN/A
Giorgia MinielloINFN Sezione di Barigiorgia.miniello@ba.infn.itN/A
Andre SznajderRio de Janeiro State Universitysznajder.andre@gmail.comN/A

How to Obtain Support

Mailbrunella.d'anzi@cern.ch,giorgia.miniello@ba.infn.it
SocialSkype: live:ary.d.anzi_1; Linkedin: brunella-d-anzi

General Information

ML/DL TechnologiesDeep Neural Networks (DNN), Random Forest (RF)
Science FieldsHigh Energy Physics
DifficultyLow
Language

English

Type

fully annotated and runnable

Software and Tools

Programming LanguagePython
ML Toolset

Tensorflow + Keras, 

Keras, Tensorflow, sklearn, rake,...

Additional librariesAdditional libraries needed, or leave empty. Ex.: uproot
Suggested EnvironmentsEnvironment needed to perform use-case. Ex.: INFN-Cloud VM, bare Linux Node, Google CoLab, otther...

Needed datasets

Data CreatorEx: CMS Experiment, Virgo, FTS, AMVA4NewPhysics, or leave empty
Data TypeWrite the source of the data. Ex: Simulation, real acquisition, other...
Data Sizedimmension of  data ued. Ex: 1GB, 8MB compressed
Data SourceWrite from where the data is available. Ex: INFN Pandora, IGWN collaboration


Short Description of the Use Case

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How to execute it

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Annotated Description

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References

Attachments