Contribute Media
A thank you to everyone who has made this possible: Read More

Sharing knowledge in the Python ecosystem


Data Scientists (or researchers) often do many early-stage prototyping and run many experiments before finding the optimal solution for the problem they are trying to solve. However, sometimes, a lot of the knowledge gained in the process stays with the person. In this proposed talk, I would like to introduce how to produce, share and ensure the reproducibility of experiments using jupyter notebooks and github. This is a series of lessons Iearned while being a research student (where open-sourcing the code and data used to generate papers is very important) and more recently, working in a new team in Zalando, where we have experimented with different ways to share and review the data science tasks, as well as the knowledge generated from those tasks.


Improve this page