08-28, 11:15–12:00 (Europe/Berlin), Room 5
Learn more about the Scientific Python project (https://scientific.python.org): what it aims to achieve (helping the developer community), recent progress that has been made, and how to become involved.
The scientific Python ecosystem comprises foundational libraries like NumPy and SciPy, technique-specific libraries like scikit-learn, NetworkX, and scikit-image, and domain-specific libraries such as PyHEP and AstroPy. The Scientific Python project is an effort to better coordinate and support the community of scientific Python ecosystem developers.
In this interactive talk, we give project updates, and invite the community to become more involved in our joint efforts to improve the ecosystem for its developers.
Learn more about the Scientific Python project, what we've done so far, and how to become involved.
Category [High Performance Computing] –Parallel Computing
Category [Community, Education, and Outreach] –Learning and Teaching Scientific Python
Category [Machine and Deep Learning] –Supervised Learning
Category [Scientific Applications] –Astronomy
Category [Data Science and Visualization] –Data Analysis and Data Engineering
Expected audience expertise: Domain –some
Expected audience expertise: Python –some
Project Homepage / Git –
Jarrod Millman is a Senior Open Source Scientific Python Developer at BIDS and the Executive Director for Berkeley's Open Source Program Office. With a background in computer science, mathematics, and statistics, and degrees from Cornell and Berkeley, Millman is a founding member of the scientific Python ecosystem. His primary focus is on developing and sustaining open-source, community-owned scientific software tools. Millman serves on the steering council of NetworkX, is a core developer of scikit-image, and was an early contributor to NumPy, SciPy, and scikit-learn. He has co-founded several influential initiatives to advance open and reproducible research, including the Scientific Python project, the nonprofit NumFOCUS, and the Neuroimaging in Python project.
I work at the intersection of computation and research, with a focus on improving open source tooling and supporting the community of developers. I've been involved with scientific Python since the early 2000s, and founded scikit-image in 2009. I am a co-author of Elegant SciPy, a community leader in the Scientific Python project (https://scientific-python.org), and thoroughly enjoy my collaborations with members of this community. I am originally from South Africa, and was privileged to attend my first EuroSciPy (which I loved!) in 2011.