https://peertube.watch/videos/watch/3c822904-8abc-443e-901a-1c2799984336 Lea is a Python module helping to calculate probabilities on situations presenting uncertainties. It is meant to be open, intuitive, and easy. Lea can deal with discrete variables, interdependent events, conditional probabilities, probabilistic programming (PP) and many more. Unlike most of other probability toolkits, it is open to different probability representations, including fractions and symbols (using the SymPy library). These features make Lea ideal for education, to learn the theory of probability, from basics to advanced concepts. The talk will present classical or non-classical problems in probability, and how these can be solved easily using Python and Lea. These include games (dice roll, RPG combats, etc.) and funny paradoxes (non-transitive dice, boy or girl paradox, etc.). The “murder party” case will demonstrate how uncertain information can help to find out the most probable perpetrator of a murder. These examples will switch between probabilities as float numbers, fractions and symbols, i.e. returning formulas instead of numbers—and demonstrating practically Python’s “duck typing” at work. The talk will conclude with a revival of the “bullshit generator”, a 15 years-old, non-serious precursor of ChatGPT (300 lines script, including data)! Speaker: Pierre Denis, Track: Python Devroom devroom, Room: UD2.218A, When: Sunday 4 February 2024, 09:30–09:55 (Brussels time), Schedule: FOSDEM 2024 event page, Slides & links Jupyter Notebook + HTML + images (slides), Licence: Creative Commons Attribution 2.0 Belgium (CC BY 2.0 BE) (as stated in the FOSDEM video archive). Attribution: “A murder party with Lea” by Pierre Denis, FOSDEM 2024. Original recording: 2024/ud2218a/fosdem-2024-2072-a-murder-party-with-lea.av1.webm from the FOSDEM video archive. This channel is an unofficial mirror; FOSDEM is a free and non-commercial event organised by the community for the community. Sun, 25 Oct 2026 01:55:05 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://peertube.watch https://peertube.watch/lazy-static/avatars/3b284627-b75f-409e-ac2e-10f4c2946f43.png https://peertube.watch/videos/watch/3c822904-8abc-443e-901a-1c2799984336 All rights reserved, unless otherwise specified in the terms specified at https://peertube.watch/about and potential licenses granted by each content's rightholder.