Best Practices in Data Annotation for AI Projects

This is online AI tech talk event, you can join from anywhere with zoom, Register and attend:
https://learn.xnextcon.com/event/eventdetails/W2020112502

Agenda:

• pre-event networking (20mins)
• community updates, jobs/interns/talents announcements. (5mins)
• tech talk (45mins)
• Q&A and closing (20mins)

Social networking with speakers, global attendees 30mins before/after the event with community update, AI jobs/intern openings, talents available announcements, etc..
Join slack by the invitation: https://bit.ly/3gi7bjf

Abstract:
We hear a lot about the importance of quality in data labeling, but it has been always difficult to find content explaining how to reach it. It is particularly harder for computer vision and NLP projects.
First of all let us ask ourselves "what is quality data labeling means"?
First things first; you need to carefully define what you need prior to deciding what you consider as a successful annotation project. This is why we center our workshop on this topic starting with the specification and what goes first in this process.
During this webinar, we will focus on computer vision projects and share a proven specifications checklist that you will be able to use for your annotation projects of computer vision. After carefully describing your annotation needs, it is far easier to set quality targets and define the annotation workflow that, by-design, secures annotation quality.

Speakers:
Jean-Emmanuel Wattier, Data Solutions Director and Head of AI/Deep Learning at Ingedata.

Networking:
30mins before/after the event on slack. Join slack by the invitation: https://bit.ly/3gi7bjf . The two channels:
#jobs for job posting from speakers, partners, sponsors companies, and you can Q&A with hiring managers right in the channel.
#events for events Q&A, mixing and networking with speakers and other peer attendees.