SciPy 2023

Andreas Mueller

Andreas Müller is a Principal Research SDE at Microsoft, where he works on the interface of the Data Science ecosystem and cloud infrastructure.
He previously held positions as Associate Research Scientist at the Columbia Data Science Institute and as a Research Engineer at the NYU Center for Data Science.
He is one of the core developers of the scikit-learn machine learning library, a member of the scikit-learn technical committee, and the author of the book "Introduction to machine learning with Python".
His work focuses on practical aspects of machine learning and the development of user-centric machine learning software.


Sessions

07-14
11:25
30min
Python Array API Standard: Toward Array Interoperability in the Scientific Python Ecosystem
Aaron Meurer, Thomas J. Fan, Stephannie Jimenez Gacha, John Kirkham, Stephan Hoyer, Tyler Reddy, Leo Fang, Matthew Barber, Ralf Gommers, Andreas Mueller, Athan Reines, Mario, Alexandre Passos, Travis E Oliphant, Saul shanabrook

The array API standard (https://data-apis.org/array-api/) is a common specification for Python array libraries, such as NumPy, PyTorch, CuPy, Dask, and JAX.

This standard will make it straightforward for array-consuming libraries, like scikit-learn and SciPy, to write code that uniformly supports all of these libraries. This will allow, for instance, running the same code on the CPU and GPU.

This talk will cover the scope of the array API standard, supporting tooling which includes a library-independent test suite and compatibility layer, what work has been completed so far, and the plans going forward.

General Track
Amphitheater 204