Workshop in deep learning application for HEP

Europe/Zurich
40/S2-A01 - Salle Anderson (CERN)

40/S2-A01 - Salle Anderson

CERN

100
Show room on map
Mohammed Mahmoud Mohammed
Description

The primary objective of the Workshop on Deep Learning and its Applications was to acquaint students with the fascinating industrial-research applications of feature engineering and machine learning techniques used in deep learning. The workshop commenced with an overview of the fundamentals of Machine Learning and Neural Networks. The resource persons provided a smooth and concise introduction to the essential preliminary concepts. The workshop covered several critical topics, such as Convolutional Neural Nets, Recurrent Neural Nets, Autoencoders, and Restricted Boltzmann Machines.

    • 08:00 12:00
      Introduction to Supervised and Unsupervised Machine Learning 4h
      Speaker: El Sayed Abdelftah Tayel (ENHEP Egyptian Network of High Energy Physics (EG))
    • 12:00 14:00
      Lunch 2h
    • 14:00 17:00
      Feed-Forward Neural Networks 3h
      Speaker: Abdurrahman Muhammed (Fayoum University (EG))
    • 08:00 12:00
      Bias and Variance in Neural Networks 4h
      Speaker: Mohammed Attia Mahmoud Mohammed (Fayoum University-Unknown-Unknown)
    • 12:00 14:00
      Lunch 2h
    • 14:00 17:00
      Convolutional Neural Networks 3h
      Speaker: Dr Ahmed Hussein (Fayoum University (EG))
    • 08:00 12:00
      Recurrent Neural Networks 4h
      Speaker: Ahmad Ahmad (Fayoum University (EG))
    • 12:00 14:00
      Lunch 2h
    • 14:00 17:00
      Generative Neural Networks 3h
    • 09:00 10:00
      Deep Learning and its Applications 1h
      Speaker: Mohammed Attia Mahmoud Mohammed (Fayoum University-Unknown-Unknown)
    • 10:00 11:00
      Modeling charged-particle multiplicity distributions at LHC 1h
      Speaker: Amr Radi (Sultan Qaboos University (OM))
    • 11:00 12:00
      Closed workshop 1h