- PyData 2022 December Edition
Welcome to the December Pydata Berlin edition!!
For everybody to feel safer, we recommend you test yourself against COVID-19 before coming to the event. A self-test or a rapid antigen test would suffice. And please refrain from coming to the event if you feel unwell.
Doors open at 18:45 and the pizzas will be served at 19:00. For security reasons GetYourGuide will only be able to welcome people until 19:30. If you arrive after 19:30 you will not be able to join the meetup. Please be on time!
The hidden beauty of relational database systems
Are you somewhat comfortable with using SQL to access data, but are curious to know what happens behind the scenes when you send off your
query? Then this is the talk for you!
Relational database systems have been around since the 1970s and they
are stacked full of cool ideas and concepts for making data handling
fast and secure. And we are still using them, nearly unchanged, 50 years
later! Reason enough, I think, to learn a bit more about how they work
and the fundamentals of their design.
Audience level: If you have played around with SQL / written some
smaller queries, you’ll be just fine.
Katharina is a freelance data scientist | computer vision engineer | teacher.
Let's exploit pickle, and skops to the rescue!
The pickle format, and loading them, has many vulnerabilities, including the fact that loading them can lead to arbitrary code execution. In this session we demonstrate what some of those exploits are, and how to create a malicious pickle file.
Then I present an alternative format from skops library which can be used to store scikit-learn based models. We talk about what the format is, and how persistence and loading is done, and what we do to prevent loading malicious objects.
Adrin is working at Hugging Face and works on skops which tackles some of the MLOps challenges related to scikit-learn models. He has a PhD in Bioinformatics, has worked as a consultant, and in an algorithmic privacy and fairness team. He's also a core developer of scikit-learn and fairlearn.
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