About the workshop
As described in the MLOSS 2018 CfP:
Machine learning open source software (MLOSS) is one of the cornerstones of open science and reproducible research. Once a niche area for ML research, MLOSS today has gathered significant momentum, fostered both by scientific community, and more recently by corporate organizations. The past mloss.org workshops, from NIPS’06 to ICML’15, successfully brought together researchers and developers from both fields, to exchange experiences and lessons learnt, to encourage interoperability between people and projects, and to demonstrate software to users in the ML community.
Continuing the tradition in 2018, this year’s workshop that is a mix of invited speakers (NumFOCUS, tidyverse, openML, GPFlow, Eigen3), contributed talks/demos, and discussion/activity sessions. This year’s headline aims to give an insight of the challenges faced by projects as they seek long-term sustainability, with a particular focus on community building and preservation, and diverse teams.
Indeed, the workshop, talks, and discussion, included speakers and participants focused on an array of programming languages from different scientific communities, and was an amazing peer-to-peer exchange of techniques and lessons learned for driving community engagement and sustainability.
Slides
Slides from my presentation (embedded, below), can also be found with working links in their GitHub repo, as well as selected resources from both the talk and the panel discussion that followed.
References
Reuse
Citation
@online{averick2018,
author = {Averick, Mara},
title = {MLOSS 2018: {Sustainable} Communities},
date = {2018-12-08},
url = {https://dataand.me/talks/2018-12_mloss-2018},
langid = {en}
}