Best Practices in Data Annotation for Quality Delivery (EMEA,APAC)

Nov 25, 02:00AM PDT(10:00AM GMT).
  • Free 160 Attendees
This session is on 25th November, 11AM CET (i.e 2:00AM PST) for audiences in Europe, Middle East, Africa and APAC regions. If you are in North America, South America, or Europe regions, register another session instead: Nov 25th, 11AM PST

We hear a lot about the importance of quality in data labeling, but it has always been difficult to find content explaining how to reach it. It is particularly harder for Computer Vision and Natural Language Processing projects. But the first and foremost question is "What does quality data labeling mean?".
To answer this, it needs to be carefully defined what you need prior to deciding what you consider as a successful annotation project. This is why we center our webinar on this topic starting with the specification and what goes first in this process.During this collaborative webinar,
we will focus on CV and NLP projects and share a proven specifications checklist that you will be able to use for your annotation projects. 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.
Jean Wattier (IngeData)

Data Solutions Director and Head of AI/Deep Learning at Ingedata. Engineer and MBA graduate, Jean created Ingedata division in AI and is in charge of developing the methodology supporting qualitative data annotation pipelines. His work consists in aligning Data Science needs with data preparation constraints at industrial scale, based on recognized certifications & research. 
Ingedata is a leading provider of data annotation to train, validate and optimize Computer Vision and Natural Language Processing models in complex cases and diverse sectors. We deliver solutions for numerous clients all over the world, leveraging high quality thanks to a unique data production methodology, our international team, and a partnership mindset. 
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