Sarah Diot-Girard
Sarah Diot-Girard has been working on Machine Learning since 2012, and she enjoys using data science tools to find solutions to practical problems. She is particularly interested in issues, both technical and ethical, coming from applying ML into real life. She gave talks at international conferences, about data privacy and algorithmic fairness, and software engineering best practices applied to data science. She is employed by Owkin as a maintainer of the Federated Learning platform Substra since 2023.
Owkin
Homepage – Twitter handle – Git*hub|lab –Session
Are you starting to use Python for scientific computing? Join this tutorial to know more about NumPy, the building block for nearly all libraries in the scientific ecosystem.
You will learn how to manipulate NumPy arrays, understand how they store data and discover how to get optimal performances. By the end of this tutorial, you will be able to start working with NumPy and know the main pitfalls to avoid.