Data Science and Machine Learning Workshop Program Introduction

Data Science and Machine Learning Workshop Program Introduction M. Gonzalez-Berges, M. Lonza 1 Data Science and Machine Learning Workshop - October 6, 2019 ICALEPCS 2019 - New York, October 5 -11, 2019

Welcome! 2 Data Science and Machine Learning Workshop - October 6, 2019 ICALEPCS 2019 - New York, October 5 -11, 2019

Workshop Motivation 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, Tensor. Flow, Keras, Py. Torch, etc or frameworks like Apache Spark, Caffe, etc) a t a d rn e d Although some examples exist of applications in accelerators and experimental physics o o m t f s o more from these l and tools. o installations, there is a feeling that we could benefit methods y t o i t l i e b c a n c The workshop is intended to give a tutorial introduction to machine learningiand tosbring up i e n l g o p i l t p l ascience and a and possiblelapplications e l t l e a n discussions on experiences of advanced data r i t o s l a physics ifacilities. n i i c f i Exp techniques i f machine learning to experimental t t r a n / e i e c c s l n e o i r t. In the morning, introductory tutorials to machine n sc will last one o The workshop full day. c tor & In the afternoon, speakers are welcome to share their learning willo benpresented. i m with presentations/demonstrations of solutions that worked or didn’t worked well. experience A final discussion will take place on possible next steps. Correlated topics: data analytics, statistical analysis, data mining, deep learning, neural networks, expert systems, automatic optimization, robotics, etc. 3 Data Science and Machine Learning Workshop - October 6, 2019 ICALEPCS 2019 - New York, October 5 -11, 2019

Timetable – Morning I 4 Data Science and Machine Learning Workshop - October 6, 2019 ICALEPCS 2019 - New York, October 5 -11, 2019

Timetable – Morning II 5 Data Science and Machine Learning Workshop - October 6, 2019 ICALEPCS 2019 - New York, October 5 -11, 2019

Timetable – Afternoon I 6 Data Science and Machine Learning Workshop - October 6, 2019 ICALEPCS 2019 - New York, October 5 -11, 2019

Timetable – Afternoon II Meet and Greet Will take place in Salon A, B, C, D, starting at 6 pm-7: 30 pm (open bar), 6 pm-8 pm (food) on Sunday, October 6 th, 2019. 7 Data Science and Machine Learning Workshop - October 6, 2019 ICALEPCS 2019 - New York, October 5 -11, 2019

Morning Tutorials ü Different ways to follow them: • Just as a presentation • Doing the tutorial exercises online − Rely on hotel wifi & free hosting services working • Following the tutorials in your computer offline. − Jupyter notebooks + Python installed 8 Data Science and Machine Learning Workshop - October 6, 2019 ICALEPCS 2019 - New York, October 5 -11, 2019

Supervised and Unsupervised Machine Learning Alfredo Canziani is a Post-Doctoral Deep Learning Research Scientist and Lecturer at NYU Courant Institute of Mathematical Sciences, under the supervision of professors Kyung. Hyun Cho and Yann Le. Cun. His research mainly focusses on Machine Learning for Autonomous Driving. Alfredo obtained both his Bachelor (2009) and Master (2011) degrees in Electrical Engineering cum laude at Trieste University, his MSc (2012) at Alfredo Canziani Cranfield University (UK), and his Ph. D (2017) at Purdue University (USA). 9 Data Science and Machine Learning Workshop - October 6, 2019 ICALEPCS 2019 - New York, October 5 -11, 2019

Reinforcement Learning Dr. Gianluca Valentino is a lecturer with the Department of Communications and Computer Engineering at the University of Malta, where he teaches in machine learning and pattern recognition. He is involved in several research projects which involve the application of these techniques in various domains, from particle accelerators to earth observation, aerospace and financial data. He spent six years with the Beams department at CERN, first as a Ph. D student working to automate the collimator beam-based alignment procedure, and then as Gianluca Valentino a postdoctoral fellow. He is currently a Visiting Scientist at CERN. 10 Data Science and Machine Learning Workshop - October 6, 2019 ICALEPCS 2019 - New York, October 5 -11, 2019

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