January 8, 2020

166 words 1 min read

I don't like notebooks.

I don't like notebooks.

I have been using and teaching Python for many years. I wrote a best-selling book about learning data science. And here's my confession: I don't like notebooks. (There are dozens of us!) I'll explain why I find notebooks difficult, show how they frustrate my preferred pedagogy, demonstrate how I prefer to work, and discuss what Jupyter could do to win me over.
Talk Title I don't like notebooks.
Speakers Joel Grus (Allen Institute for Artificial Intelligence)
Conference JupyterCon in New York 2018
Conf Tag The Official Jupyter Conference
Location New York, New York
Date August 22-24, 2018
URL Talk Page
Slides Talk Slides
Video

I have been using and teaching Python for many years. I wrote a best-selling book about learning data science. And here’s my confession: I don’t like notebooks. (There are dozens of us!) I’ll explain why I find notebooks difficult, show how they frustrate my preferred pedagogy, demonstrate how I prefer to work, and discuss what Jupyter could do to win me over.

teaching data science jupyter python book
comments powered by Disqus
JupyterHub for domain-focused integrated learning modules

JupyterHub for domain-focused integrated learning modules

January 7, 2020

The Data Science Modules program at UC Berkeley creates short explorations into data science using notebooks to allow students to work hands-on with a dataset relevant to their course. Mariah Rogers, Ronald Walker, and Julian Kudszus explain the logistics behind such a program and the indispensable features of JupyterHub that enable such a unique learning experience.
nbinteract: Shareable interactive web pages from notebooks

nbinteract: Shareable interactive web pages from notebooks

January 7, 2020

The nbinteract package converts Jupyter notebooks with widgets into interactive, standalone HTML pages. Its built-in support for function-driven plotting makes authoring interactive pages simpler by allowing users to focus on data, not callbacks. Sam Lau and Caleb Siu offer an overview of nbinteract and walk you through the steps to publish an interactive web page from a Jupyter notebook.
Reproducible data dependencies for Jupyter: Distributing massive, versioned image datasets from the Allen Institute for Cell Science

Reproducible data dependencies for Jupyter: Distributing massive, versioned image datasets from the Allen Institute for Cell Science

January 6, 2020

Reproducible data is essential for notebooks that work across time, across contributors, and across machines. Jackson Brown and Aneesh Karve demonstrate how to use an open source data registry to create reproducible data dependencies for Jupyter and share a case study in open science over terabyte-size image datasets.
Human-in-the-loop data science with Jupyter widgets

Human-in-the-loop data science with Jupyter widgets

December 8, 2019

Jupyter widgets let you create lightweight, interactive graphical interfaces directly in Jupyter notebooks. Pascal Bugnion demonstrates how to use Jupyter widgets to implement human-in-the-loop machine learning with highly interactive user interfaces.
Jupyter for every high schooler

Jupyter for every high schooler

January 8, 2020

In an effort to broaden graduates' mathematical toolkit and address gender equity in STEM education, Rob Newton has led the implementation of Python projects across his school's entire ninth-grade math courses. Now every student in the ninth grade completes three python projects that introduce programming and integrate them with the ideas developed in class.
Jupyter notebooks and the intersection of data science and data engineering

Jupyter notebooks and the intersection of data science and data engineering

January 7, 2020

David Schaaf explains how data science and data engineering can work together in cross-functional teamswith Jupyter notebooks at the center of collaboration and the analytic workflowto more effectively and more quickly deliver results to decision makers.