The Jupyter ecosystem gives users an ever-growing set of superpowers for working with data. Jupyter enables users to interactively explore and visualize data, schedule jobs, and share their work in reproducible notebooks. Jupyter’s open standards, formats, and protocols make all this possible.
M Pacer discusses two meanings of “Talking with Jupyter”: talking to others with Jupyter notebooks and talking to Jupyter in the language of its standards, formats, and protocols. M describes tools, workflows, and patterns that make both kinds of talking with Jupyter easier while unlocking new ways of interacting with the Jupyter ecosystem.
M Pacer is a Jupyter core developer and a senior notebook engineer at Netflix. Previously, M was a postdoctoral researcher the Berkeley Institute for Data Science (BIDS), focusing on the intersection between Jupyter and scientific publishing. M holds a PhD from UC Berkeley, where their research used machine learning and human experiments to study casual explanation and causal inference, and a BS from Yale University, where their research focused on the role of causal language in evaluating scientific claims.
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