Version 0.12 Aug. 28, 2024
We released a new schedule version!
Version 0.11 Aug. 24, 2024
We released a new schedule version!
We have a new session: “Using Wikipedia as a language corpus for NLP” by Jakub B. Jagiełło.
We have moved a session around: “Introduction to Machine Learning with scikit-learn and Pandas” by Justyna Szydłowska-Samsel (Aug. 27, 2024, 11 a.m. → Aug. 27, 2024, 2 p.m.)
Version 0.10 Aug. 13, 2024
We released a new schedule version!
We sadly had to cancel a session: “Architecting Science Tools: A Roadmap for Turning Theory and Data Projects into Python Packages” by Ramon Perez
Version 0.9 Aug. 6, 2024
We released a new schedule version!
We have new sessions!
- “What is the magic of magic methods in the Python language?” by Paweł Żal
- “Introduction to Machine Learning with scikit-learn and Pandas” by Justyna Szydłowska-Samsel
We had to move some sessions, so if you were planning on seeing them, check their new dates or locations:
- “Probabilistic classification and cost-sensitive learning with scikit-learn” by Guillaume Lemaitre, Olivier Grisel (Aug. 26, 2024, 11 a.m. → Aug. 26, 2024, 2 p.m.)
- “Decorators - A Deep Dive” by Mike Müller (Aug. 26, 2024, 4 p.m. → Aug. 26, 2024, 11 a.m.)
- “Using the Array API to write code that runs with Numpy, Cupy and PyTorch” by Tim Head, Sebastian Berg (Aug. 26, 2024, 2 p.m. → Aug. 26, 2024, 4 p.m.)
Version 0.8 July 26, 2024
We released a new schedule version!
We have a new session: “Just contribute?!” by Wolf Vollprecht.
Version 0.7 July 23, 2024
We released a new schedule version!
We have new sessions!
- “Scientific Python” by Jarrod Millman, Stéfan van der Walt
- “[CHANGE OF PROGRAM] Informal discussions about switching build backends” by Ralf Gommers
- “Dispatching, Backend Selection, and Compatibility APIs” by Guillaume Lemaitre, Joris Van den Bossche, Tim Head, Erik Welch, Marco Gorelli, Sebastian Berg, Aditi Juneja, Stéfan van der Walt
Version 0.6 July 22, 2024
We released a new schedule version!
We sadly had to cancel a session: “Blazing Speed and Efficiency in Data Analytics with DuckDB and Python” by Aditya Mehra
We had to move some sessions, so if you were planning on seeing them, check their new dates or locations:
- “OpenGL is dying, let's talk about WebGPU” by Almar Klein (Aug. 28, 2024, 2:15 p.m. → Aug. 28, 2024, 10:30 a.m.)
- “The joys and pains of reproducing research: An experiment in bioimaging data analysis” by Marianne Corvellec (Aug. 28, 2024, 1:55 p.m. → Aug. 28, 2024, 1:20 p.m.)
- “Conformal Prediction with MAPIE: A Journey into Reliable Uncertainty Quantification” by Claudio G. Giancaterino (Aug. 28, 2024, 2:40 p.m., Room 7 → Aug. 28, 2024, 2:25 p.m., Room 6)
- “Mostly Harmless Fixed Effects Regression in Python with PyFixest” by Alexander Fischer (Aug. 28, 2024, 2:30 p.m. → Aug. 28, 2024, 1:55 p.m.)
- “A Qdrant and Specter2 framework for tracking resubmissions of rejected manuscripts in academia” by Daniele Raimondi (Aug. 28, 2024, 2:15 p.m. → Aug. 28, 2024, 2:25 p.m.)
- “Free-threaded (aka nogil) CPython in the Scientific Python ecosystem : status and road ahead” by Loïc Estève (Aug. 29, 2024, 11:30 a.m., Room 6 → Aug. 29, 2024, 3:30 p.m., Room 7)
- “forecasting foundation models: evaluation and integration with sktime – challenges and outcomes” by Franz Kiraly, Benedikt Heidrich (Aug. 29, 2024, 3:30 p.m. → Aug. 29, 2024, 11 a.m.)
- “NumPy's new DType API and 2.0 transition” by Sebastian Berg (Aug. 29, 2024, 11:30 a.m. → Aug. 29, 2024, 11 a.m.)
- “The Array API Standard in SciPy” by Lucas Colley (Aug. 29, 2024, 11:05 a.m., Room 7 → Aug. 29, 2024, 11:30 a.m., Room 6)
Version 0.5 July 19, 2024
We released a new schedule version!
We have new sessions!
- “OpenGL is dying, let's talk about WebGPU” by Almar Klein
- “Image analysis in Python with scikit-image” by Lars Grüter, Marianne Corvellec, Stéfan van der Walt
We had to move some sessions, so if you were planning on seeing them, check their new dates or locations:
- “Introduction to matplotlib for Data Visualization with Python” by Nefta Kanilmaz (Aug. 27, 2024, 11 a.m. → Aug. 26, 2024, 2 p.m.)
- “Introduction to Python” by Mojdeh Rastgoo (Aug. 26, 2024, 11 a.m. → Aug. 26, 2024, 9 a.m.)
- “Introduction to NumPy” by Sarah Diot-Girard (Aug. 26, 2024, 2 p.m. → Aug. 26, 2024, 11 a.m.)
Version 0.4 July 15, 2024
We released a new schedule version!
We had to move some sessions, so if you were planning on seeing them, check their new dates or locations:
- “Helmholtz Blablador and the LLM models' ecosystem” by Alexandre Strube (Aug. 29, 2024, 3:30 p.m. → Aug. 28, 2024, 11:05 a.m.)
- “A Comparative Study of Open Source Computer Vision Models for Application on Small Data: The Case of CFRP Tape Laying” by Thomas Fraunholz, Tim Köhler (Aug. 28, 2024, 11:05 a.m. → Aug. 29, 2024, 4 p.m.)
- “forecasting foundation models: evaluation and integration with sktime – challenges and outcomes” by Franz Kiraly, Benedikt Heidrich (Aug. 29, 2024, 4 p.m. → Aug. 29, 2024, 3:30 p.m.)
Version 0.3 July 15, 2024
We released a new schedule version!
Version 0.2 July 15, 2024
We released a new schedule version!
We have new sessions!
- “From data analysis in Jupyter Notebooks to production applications: AI infrastructure at reasonable scale” by Frank Sauerburger
- “forecasting foundation models: evaluation and integration with sktime – challenges and outcomes” by Franz Kiraly, Benedikt Heidrich
- “sktime - python toolbox for time series – introduction and new features 2024: foundation models, deep learning backends, probabilistic models, hierarchical demand forecasting, marketplace features” by Franz Kiraly, Felipe Angelim, Muhammad Armaghan Shakir, Benedikt Heidrich
- “Probabilistic classification and cost-sensitive learning with scikit-learn” by Guillaume Lemaitre, Olivier Grisel
- “Introduction to NumPy” by Sarah Diot-Girard
- “10 Years of Open Source: Navigating the Next AI Revolution” by Ines Montani
- “Reproducible workflows with AiiDA - The power and challenges of full data provenance” by Marnik Bercx, Xing Wang
- “Enhancing Bayesian Optimization with Ensemble Models for Categorical Domains” by Ilya Komarov
- “Accelerating Python on HPC with Dask” by Jacob Tomlinson
- “Free-threaded (aka nogil) CPython in the Scientific Python ecosystem : status and road ahead” by Loïc Estève
- “The Parallel Universe in Python - A Time Travel to Python 3.13 and beyond” by Mike Müller
- “Helmholtz Blablador and the LLM models' ecosystem” by Alexandre Strube
- “Regularizing Python using Structured Control Flow” by Valentin Haenel
- “wgpu and pygfx: next-generation graphics for Python” by Almar Klein
- “Optimagic: Can we unify Python's numerical optimization ecosystem?” by Janos Gabler
- “Introduction to Python” by Mojdeh Rastgoo
- “Introduction to Polars: Fast and Readable Data Analysis” by Geir Arne Hjelle
- “Architecting Science Tools: A Roadmap for Turning Theory and Data Projects into Python Packages” by Ramon Perez
- “A Qdrant and Specter2 framework for tracking resubmissions of rejected manuscripts in academia” by Daniele Raimondi
- “Mostly Harmless Fixed Effects Regression in Python with PyFixest” by Alexander Fischer
- “Federated Learning: Where we are and where we need to be” by Katharine Jarmul
- “Blazing Speed and Efficiency in Data Analytics with DuckDB and Python” by Aditya Mehra
- “The Array API Standard in SciPy” by Lucas Colley
- “Simulated data is all you need: Bayesian parameter inference for scientific simulators with SBI” by Jan Boelts (Teusen)
- “A Comparative Study of Open Source Computer Vision Models for Application on Small Data: The Case of CFRP Tape Laying” by Thomas Fraunholz, Tim Köhler
- “Understanding NetworkX's API Dispatching with a parallel backend” by Erik Welch, Aditi Juneja
- “Multi-dimensional arrays with Scipp” by Mridul Seth
- “fastplotlib: A high-level library for ultra fast visualization of large datasets using modern graphics APIs” by Kushal Kolar, Caitlin Lewis
- “From stringly typed to strongly typed: Insights from re-designing a library to get the most out of type hints” by Janos Gabler
- “Combining Python and Rust to create Polars Plugins” by Marco Gorelli
- “The joys and pains of reproducing research: An experiment in bioimaging data analysis” by Marianne Corvellec
- “napari: multi-dimensional image visualization, annotation, and analysis in Python” by Grzegorz Bokota, Wouter-Michiel Vierdag
- “A Hitchhiker's Guide to Contributing to Open Source” by Sebastian Berg, Nikoleta E. Glynatsi
- “Decorators - A Deep Dive” by Mike Müller
- “Skrub: prepping tables for machine learning” by Guillaume Lemaitre, Vincent Maladiere, Jérôme Dockès
- “The Mission Support System and its use in planning an aircraft campaign” by Reimar Bauer
- “Introduction to matplotlib for Data Visualization with Python” by Nefta Kanilmaz
- “Data augmentation with Scikit-LLM” by Claudio G. Giancaterino
- “Using the Array API to write code that runs with Numpy, Cupy and PyTorch” by Tim Head, Sebastian Berg
- “LPython: Novel, Fast, Retargetable Python Compiler” by Naman Gera
- “NumPy's new DType API and 2.0 transition” by Sebastian Berg
We had to move some sessions, so if you were planning on seeing them, check their new dates or locations:
- “Building robust workflows with strong provenance” by Alexander Goscinski, Julian Geiger, Ali Khosravi (Aug. 26, 2024, 10:30 a.m., Room 7 → Aug. 27, 2024, 9 a.m., Room 5)
- “Conformal Prediction with MAPIE: A Journey into Reliable Uncertainty Quantification” by Claudio G. Giancaterino (Aug. 26, 2024, 9:30 a.m. → Aug. 28, 2024, 2:40 p.m.)
- “Building optimized packages for conda-forge and PyPI” by Wolf Vollprecht, Bas Zalmstra (Aug. 26, 2024, 10 a.m., Room 7 → Aug. 29, 2024, 2:30 p.m., Room 6)
Version 0.1 July 3, 2024
We released a new schedule version!
We have new sessions!
- “Building robust workflows with strong provenance” by Alexander Goscinski, Julian Geiger, Ali Khosravi
- “Conformal Prediction with MAPIE: A Journey into Reliable Uncertainty Quantification” by Claudio G. Giancaterino
- “Building optimized packages for conda-forge and PyPI” by Wolf Vollprecht, Bas Zalmstra
Version 0.0 July 3, 2024
We released our first schedule!