Insider Tips on Data Annotation Project Management
Collaboration & Project Management for data scientists and ML engineers
November 29th, 2022 - 5:00 p.m CEST / 11:00 a.m EDT - English
85% of ALL machine learning projects NEVER reach real-world deployment – most often due to a lack of excellent-quality training data!
To be fair, getting this excellent-quality training data through data annotation is no picnic. A labeling project is much more complex than a normal ML project. Scoping, processes, teams, timelines: the opportunities to fail are numerous and the cost in time and budget is huge.
As a fellow machine learning engineer, and as the former Head of AI at BNP Paribas, our co-founder and CTO Edouard knows where you stand. Before co-founding Kili Technology, he built one of the most advanced AI labs in Europe from the ground and faced the same challenge.
That’s why he’ll hold this session on how to adopt an industry-leading approach to managing and delivering successful data annotation projects.
- his learnings on the most common reasons why your data annotation project doesn't perform;
- and his end-to-end recipe to scope and execute a data annotation project smoothly.
Register to attend
Chief Technology Officer
@ Kili Technology
“But the real-world experience of those who put them into production shows that (...) it's often the quality of
data (...) that makes your AI project succeed or fail.”