Valerio Maggio
Valerio Maggio is a Researcher, and a Data scientist Advocate at Anaconda. He is well versed in open science and research software, supporting the adoption of best software development practice (e.g. Code Review) in Data Science. He has been recently awarded a fellowship from the Software Sustainability Institute (profile) focused on developing open teaching modules [1][2] on Privacy-Preserving Machine learning technologies. Valerio is also an open-source contributor, and an active member of the Python community. Over the last twelve years he has contributed and volunteered in the organization of many international conferences and community meetups like PyCon Italy, PyData, EuroPython, and EuroSciPy. All his talks, workshop materials and open source contributions are publicly available on his Speaker Deck and GitHub profiles.
Anaconda, inc
Session
Privacy guarantee is the most crucial requirement when it comes to analyse sensitive data. However, data anonymisation techniques alone do not always provide complete privacy protection; moreover Machine Learning models could also be exploited to leak sensitive data when attacked, and no counter-measure is applied. Privacy-preserving machine learning (PPML) methods hold the promise to overcome all these issues, allowing to train machine learning models with full privacy guarantees. In this tutorial we will explore several methods for privacy-preserving data analysis, and how these techniques can be used to safely train ML models without actually seeing the data.