Marcello Politi
Machine Learning Scientist at Pi School- Claim this Profile
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Bio
Credentials
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Mathematics for Machine Learning
Imperial College LondonDec, 2022- Oct, 2024 -
Living Planet Symposium 2022 - Certificate of Attendance
European Space Agency - ESAJun, 2022- Oct, 2024 -
Pandas
KaggleDec, 2021- Oct, 2024 -
Computer Vision
KaggleNov, 2021- Oct, 2024 -
Intro to Deep Learning
KaggleNov, 2021- Oct, 2024 -
Data Cleaning
KaggleOct, 2021- Oct, 2024 -
Intermediate Machine Learning
KaggleSep, 2021- Oct, 2024 -
Intro to Machine Learning
KaggleSep, 2021- Oct, 2024 -
C# Unity Game Developer 2D
UdemySep, 2020- Oct, 2024 -
C# Unity Game Developer 3D
UdemySep, 2020- Oct, 2024 -
Machine Learning By Standford University
CourseraSep, 2020- Oct, 2024 -
Java EE Developer
UdemyJan, 2019- Oct, 2024 -
Arduino course
FabLab LazioMar, 2017- Oct, 2024 -
Advanced Computer Vision
Courser -
Advanced English Course
Berlitz Corporation -
CUDA C++ Masterclass
Udemy -
Flutter for IOS & Android Apps
Udemy
Experience
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Pi School
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Italy
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Professional Training and Coaching
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1 - 100 Employee
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Machine Learning Scientist
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Feb 2023 - Present
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Space Generation Advisory Council
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Austria
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Aviation and Aerospace Component Manufacturing
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200 - 300 Employee
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Member & Event Manager
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Jul 2022 - Present
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Eyedea Recognition Ltd.
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Czechia
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Software Development
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1 - 100 Employee
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Machine Learning Specialist
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Nov 2022 - Mar 2023
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European Space Agency - ESA
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France
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Space Research and Technology
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700 & Above Employee
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Software Engineer (YGT)
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Sep 2021 - Sep 2022
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Inria
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France
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Research Services
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700 & Above Employee
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Deep Learning Researcher
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Mar 2021 - Jul 2021
The internship aims at tackling the problem of compressing artificial neural networks via iterative pruning approaches. I will review state-of-the-art approaches, devise variants of known methods and possibly design novel approaches, and extensively validate those methods against known ones. Iterative pruning methods have been a classical approach for neural network compression since several decades. While earlier methods relied on heuristic arguments, such as assumptions on the Taylor approximation of the loss function, recent approaches have attempted to provide rigorous guarantees by leveraging algorithmic techniques. The project will focus on the assessment of the merits and shortcomings of such recent contributions, and possibly derive novel approaches based on algorithmic insights. The proposed implementation language for the project is the Julia language. Show less
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Data Analyst
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Sep 2020 - Feb 2021
Intern at ESRIN for the Common Services Section (EOP-GES) Tasks description: •Analyse website data on traffic patterns, behaviour, navigation and user flows •Answer key questions through statistical analyses, reporting and dashboards using analytics toolset •Share data views to enable responsible staff to optimize decision making •Analyse internet trends to identify future technology needs and internet patterns •Identify methodologies and technologies for data and content linking •Advise on Search Engine Optimisation and best practice using the Search Engine Console tool •Assist in the review of the ESA Earth Observation Web Development Guidelines Show less
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Eustema S.p.A.
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Italy
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IT Services and IT Consulting
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300 - 400 Employee
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Professional Course Java EE
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Feb 2019 - Mar 2019
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Università di Roma Tor Vergata
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Technology, Information and Internet
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1 - 100 Employee
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Hackathon Tor Vergata 2019 - Organizer
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Jan 2019 - Mar 2019
- Website creator- Logistic- Development of competition themes
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Scolarship holder
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2019 - 2019
During this period I delevoped a mobile application using Flutter for the department of Physics of the University of Tor Vergata
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Education
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Università di Roma Tor Vergata
Master of Science - MS, Computer Science -
Pi School
School of Artificial Intelligence -
Deep Learning Italia
Advanced Master, Deep Learning -
Dock3 - The Startup Lab
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Università di Roma Tor Vergata
Bachelor of Science - BS, omputer Science