In this episode of DataFramed, Hugo speaks with Brian Granger, co-founder and co-lead of Project Jupyter, physicist and co-creator of the Altair package for statistical visualization in Python.

They’ll speak about data science, interactive computing, open source software and Project Jupyter. With over 2.5 million public Jupyter notebooks on github alone, Project Jupyter is a force to be reckoned with. What is interactive computing and why is it important for data science work? What are all the the moving parts of the Jupyter ecosystem, from notebooks to JupyterLab to JupyterHub and binder and why are they so relevant as more and more institutions adopt open source software for interactive computing and data science? From Netflix running around 100,000 Jupyter notebook batch jobs a day to LIGO’s Nobel prize winning discovery of gravitational waves publishing all their results reproducibly using Notebooks, Project Jupyter is everywhere.

Links from the show

FROM THE INTERVIEW

FROM THE SEGMENTS

Machines that Multi-Task (with Friederike Schüür of Fast Forward Labs)Part 1 at ~24:40

Part 2 at ~44:00

Rich Caruana’s Awesome Overview of Multi-Task Learning and Why It Works
Sebastian’s Ruder’s Overview of Multi-Task Learning in Deep Neural Networks
Massively Multi-Task Network for Drug Discovery, 259 Tasks (!) (Ramsundar et al. arXiv.org)
Brief Overview of Multi-Task Learning with Video of Newsie, the Prototype (By Friederike Schüür)

Original music and sounds by The Sticks.

#44 Project Jupyter and Interactive Computing

DataFramed