Though machine learning and AI are immensely powerful, these solutions are by no means easy. In many cases, there are many diverse components that are not designed to work together. Additionally, thes …

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.

Climate science is being flooded with petabytes of data, overwhelming traditional modes of data analysis. The Pangeo project is building a platform to take big data climate science into the cloud using SciPy and large-scale interactive computing tools. Join Ryan Abernathey and Yuvi Panda to find out what the Pangeo team is building and why and learn how to use it.

The key to successful threat detection in cybersecurity is fast response. George Williams, Harini Kannan, and Alex Comerford offer an overview of specialized extensions they have built for data scientists working in cybersecurity that can be used and deployed via JupyterHub.

In 2018, UC Berkeley launched a new major in data science, anchored by two core courses that are the fastest-growing in the history of the university. Fernando Prez discusses the program and explains how the core courses, which now reach roughly 40% of the campus population, are extending data science into specific domains that cover virtually all disciplinary areas of the campus.

In Capital One's recent exploration of "notebook" offerings, JupyterHub emerged as a top contender that could serve as a potential platform for analytics even in highly regulated industries like financial services. David Schaaf and Shivraj Ramanan discuss Capital One's journey and explain how Jupyter has become a part of the company's ever-growing analytics toolkit.

How do you bootstrap an open source project that aims to provide stability, composability, and portability for machine learning? You use Kubernetes and its rich ecosystem to implement the pieces of in …