Second ML-INFN Hackathon: Starting Level

Contribution List

15. Introduction and logistics

Tommaso Boccali (PI)

13/12/2021, 09:00

1. What is Machine Learning and why it is relevant for research?

Maurizio Pierini (CERN)

13/12/2021, 09:20

Introduction

2. Neural Networks: principles and common architectures

Stefano Giagu (ROMA1)

13/12/2021, 10:10

Introduction

4. INFN-Cloud, and how to use it for ML_INFN

Daniele Spiga (PG)

13/12/2021, 11:30

Introduction

6. Hands-on - Playing with CERN Open Data with numpy, pandas and pyplot

Lucio Anderlini (FI)

13/12/2021, 13:45

Hands-on

7. Introduction to keras

Andrea Rizzi (INFN Pisa), Andrea Rizzi (PI)

13/12/2021, 15:00

Hands-on

8. Hands-on - Introduction to keras

Andrea Rizzi (PI), Andrea Rizzi (INFN Pisa)

13/12/2021, 15:30

Hands-on

11. ML for applications in High Energy Physics

Tommaso Boccali (Istituto Nazionale di Fisica Nucleare)

14/12/2021, 09:00

9. ML Basics: hands-on on a simple categorization example in HEP

Lucio Anderlini (FI)

14/12/2021, 09:50

10. ML for applications in medical physics of INFN interest

Alessandra Retico (PI)

14/12/2021, 12:40

12. Discrimination of hadronic jets from light and heavy flavours @ LHC

Tommaso Boccali (PI)

15/12/2021, 09:00

Hackathon introduction

17. Signal/background discrimination for the VBF Higgs four lepton decay channel with the CMS experiment

Brunella D'Anzi (Istituto Nazionale di Fisica Nucleare)

15/12/2021, 09:10

Hackathon introduction

13. Autoencoders for VIRGO GW signal analysis

Francesco Di Renzo (P)

15/12/2021, 09:20

Hackathon introduction

14. Classification of lesions in medical physics

Alessandra Retico (PI)

15/12/2021, 09:30

Hackathon introduction

3. Cloud Computing and Cloud-INFN

Introduction

16. How to access INFNCloud

Daniele Spiga (PG), Doina Cristina Duma (CNAF)

5. Playing with CERN Open Data with numpy, pandas and pyplot

Lucio Anderlini (FI)

Hands-on