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Second ML-INFN Hackathon: Starting Level
→
Europe/Rome
http://cern.ch/go/pk7C (Zoom)
http://cern.ch/go/pk7C
Zoom
Direct link :
https://cern.zoom.us/j/63455648268?pwd=T0UrY1VHMGhqK21BSFdXZC8rQ05xUT09
The Meeting ID is 634 5564 8268 with the passcode 11111
Description
Welcome to the second edition of the Machine Learning @ INFN (ML_INFN) starting level hackathon, dedicated to INFN Affiliates.
Registration is now closed.
You can see the first edition here, with most of the talks attached as video files.
The course is to be considered as "starting level" for Machine Learning topics.The hackathon will be organized over 3 days, distributed as
- General introduction on ML and on its use in INFN (including Clouds)
- Tutored hands-on of specific use cases, attempting to reach fully working products; a review of the ML utilization in specific use cases of INFN interest
- The hackathon, with participants working in groups trying to achieve a goal in the form of a realistic analyses. In the latter part, presentation of their work is expected and discussed among all the groups.
The use cases for third day ("hackathon")
Upon registration, users will be asked to express a first and second preference for a one of the use cases offered. We will try to
- whenever possible, satisfy the preference in the order given
- try to form groups with students with the full range of proficiencies, in order to allow for self-tutoring inside the groups
The list of available use cases for the hackathon are currently (there could be additions depending on the registration process and on the status of other opportunities):
- Signal / Background discrimination @ LHC: b Tagging AND Higgs Boson Searches
- autoencoders for VIRGO GW signal analysis
- classification of lesions in medical physics
Prerequisites
Technical: access to INFN Cloud provided resources
NOTE: users will use INFN-Cloud resources and this does not require any specific INFN-Cloud authorization.
Please read and comply with the recommendations in the side menu "technical prerequisite".
Machine learning related knowledge
The hackathon is to be considered as entry level for Machine Learning. Still, some fluency in the tools to be used is a prerequisite and it is needed to speed up the tutoring. In particular, we expect:
- some fluency in Python:
- basic program flow, definition and use of variables
- definition and utilization of functions
- package management (import, install via pip)
- some fluency in numpy:
- arrays, basic operations, reshaping
- some fluency on matplotlib:
- how to define and plot a basic figure
- some fluency on online python notebooks
- (like SWAN, Jupyter, Google Colab)
In case you do not feel proficient enough in the previous items, we suggest a list of entry level tutorial / documentation we advise to read and test before the Hackathon, in order to be able to follow with profit the presentations and the hands-on. This can be found in the side menu, at the entry "Pre-tutorial Self-teaching".
Registration
Attending the hackathon is free and happens via the entry in the side menu.
The number of participants can be limited, depending on the tutoring and technical capabilities.
Upon registration, we will require:
- INFN Affiliation
- Research interests
- Proficiency level in Machine Learning and related tools
- Specific interests in Machine learning techniques
- The preferred use case for the third day (first and second choice)
Additional Material
Please consider visiting again this page from time to time: we will add more resources for the hackathon and related projects as soon as they become available,.
Participants
Alberto Annovi
Alessandro De Falco
Alessandro Di Mattia
Alessandro Renzi
Alessio Fiori
Amodio Carleo
Andrea Maino
Andrea Massironi
Annalisa Mastroserio
Antonio D'Avanzo
Antonio Palasciano
Antonio Sidoti
Benedetta Camaiani
Cristiano Palomba
Daniele Massaro
Diana Domenichini
Elizabeth Long
Elvira Rossi
Emanuele Leonardi
Enrico Catanzani
Fabio Colamaria
Francesco Cirotto
Francesco Faldi
Gabriele Martelli
Germano Bonomi
Giacomo Levrini
Gianfranco Paternò
Giovanni Di Domenico
Giovanni Francesco Tassielli
Giuseppe La Vacca
Giuseppe Messineo
Henrik Munch
Ian Postuma
Leandro Javier Cieri
Leonardo Cristella
Lisa Rinaldi
LORENZO MACCONE
Lorenzo Mirasola
Marco Corvo
Marco Rocchini
Marco Serra
Maria Artero Pons
Marta Urioni
Mateusz Bawaj
Matteo Presilla
Matteo Tenti
Michela Lai
Mirko Massi
Nicoletta Protti
Paolo Mastrandrea
Pia Astone
Pierluigi Bortignon
Pietro Cortese
Raffaella Cabini
Riccardo Lollini
Roberto Franceschini
Samrangy Sadhu
Samuele Millesoli
Sara Rastello
Silvia Auricchio
Stefano Dusini
Tommaso Diotalevi
Surveys
ML_INFN Second Hackathon Survey
Contact
