Workshop Description
The fields of large scale data analytics and machine learning have made impressive progress in recent years. Many applications have been successful in applying techniques in these fields for problems in areas such as health, language processing, search engines, etc Many tools have been developed to facilitate the application of these techniques (e.g. libraries like Scikit-learn, TensorFlow, Keras, PyTorch, Apache Spark, etc)
A growing number of examples of applications in accelerators and experimental physics installations have started to appear in the last years. The workshop will aim to share the experience gained in the development of some of these applications, whether successful or not. This should contribute to the continuous growth of the use of these methods in our systems.
Correlated topics: data analytics, statistical analysis, data mining, deep learning, neural networks, expert systems, automatic optimization, robotics, etc.
Organizational Details:
Given the conference limitations due to Covid, the workshop will last only half day, from 12:00 to 16:00 (UTC) 15th October.
We have decided not to include any tutorials. As a pre-workshop activity, you can follow the tutorials of the previous edition from the Indico site: https://indico.cern.ch/event/828418/. For the tutorials of Alfredo Canziani on Supervised and Unsupervised learning (or other related topics), you can go directly to his YouTube channel (link below)
We are at the moment preparing the agenda. Despite the big number of participants and the remote format, we aim to have the workshop as interactive as possible. We will start with an introductive session where experts will give us an overview of techniques and applications in the field. This will be followed by informal presentations by the participants aiming to trigger discussions among all of us. We are not expecting fully polished presentations like in the conference, but rather short presentations of problems that you have solved, failed to solve or are trying to face using data science or machine learning. If you have a proposal for a contribution, please submit a short abstract in this Indico page (left menu). Please indicate also the time you would need for the presentation.
For the abstract submission you will need to login to the Indico page with either your CERN credentials, your organization credential if it is part of EduGAIN, or with your public service account (e.g. Facebook, Google, etc.). If you experience any issue with the submission, you can send the abstract via email to:
manuel.gonzalez@cern.ch and marco.lonza@elettra.eu
Reference links:
ICALEPCS 2021 Official Page: https://indico.ssrf.ac.cn/event/1/
ICALEPCS 2021 Workshops: https://indico.ssrf.ac.cn/event/1/page/16-workshops
Alfredo Canziani YouTube channel: https://www.youtube.com/c/AlfredoCanziani/videos
