2019:Technology outreach & innovation/The hurdles of deploying Machine Learning models in production
![]() | This is a Closed submission for Wikimania 2019. It has been reviewed and was not accepted. |
Description
Deploying Machine Learning applications in a production environment poses significant hurdles that the movement hasn't been called to address in a consistent and concise manner up to now. Some adhoc solutions exists. This talk is about identifying those issues, spreading knowledge and proposing solutions.
Relationship to the theme
This session will address the conference theme — Wikimedia, Free Knowledge and the Sustainable Development Goals — in the following manner:
- 8 - Decent work and economic growth
- 9 - Industry, Innocation and Infrastructure
Session outcomes
At the end of the session, the following will have been achieved:
- The major hurdles to deploying machine learning applications in a production environment will be understood by the audience
- Possible solutions to those issues will have been shown and pros and cons discussed
- Developers interested in having machine learning applications deployed in the movement's infrastructure will have a clear understanding of the requirements
Session leader(s)
- Alexandros Kosiaris
Contacts
- akosiaris@wikimedia.org, IRC: akosiaris
Session type
Each Space at Wikimania 2019 will have specific format requests. The program design prioritises submissions which are future-oriented and directly engage the audience. The format of this submission is a:
- Lecture
Requirements
The session will work best with these conditions:
- Room:
- Class room or lecture hall.
- Projector and screen
- Audience:
- 30-50.
- Being/wanting to become a developer with an interest in deploying an application into the movement's production environment a plus
- Recording:
- Freely licensed slides, straight forward presentation, no limitations.