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Discover Project Jupyter, a nonprofit dedicated to developing open-source software, open standrad and services for interactive computing. Join associate professor Brian Granger during this invited talk, hosted by associate professor Violet R. Syrotiuk.
Invited Talk: Project Jupyter: From Computational Notebooks to Large-Scale Data Science and Machine Learning
Monday, October 1, 2018
10:30 a.m.
Brickyard Engineering (BYENG) 420, Tempe campus [map]
Abstract
Project Jupyter is an open-source project that exists to develop software, open standards and services for interactive and reproducible computing. The main application developed is the Jupyter Notebook, a web application that allows users to create documents that combine live code with narrative text, mathematical equations and visualizations. Since its creation in 2011, the Jupyter Notebook has become a widely-used open standard for developing, sharing, communicating and reproducing computational work in scientific computing and data science.
In this talk, Granger overviews Project Jupyter and its open-source software and open standards for interactive and exploratory computing. There are many examples across industries, disciplines and organizations that will illustrate Jupyter’s main principles. Learn about Jupyter’s current work on JupyterLab, JupyterHub and Binder and see how it is leading to
- new challenges with large scale data science within complex organizations.
- legal, ethical and technical questions regarding sensitive data.
- new opportunities for human-centered design of machine learning systems.
About the Speaker
Brian Granger is an associate professor of physics and data science at Cal Poly State University in San Luis Obispo, California. His research focuses on building open-source tools for interactive computing, data science and data visualization. Granger is a co-founder of Project Jupyter, a leader of IPython, co-founder of the Altair project for statistical visualization and an active contributor to a number of other open-source projects focused on data science in Python. He is an advisory board member of NumFOCUS and a faculty fellow of the Cal Poly Center for Innovation and Entrepreneurship.
