Webinar
Automation in Data Labeling:
How To Label Faster Without Compromising Quality?
February 23rd, 2023 - 5:00 P.M CEST / 11:00 A.M EDT - English
If you’re working in Machine Learning, you know that building training datasets is a long and tedious task. Many ways to make the labeling process faster are possible by automating steps.
In this webinar, our Head of Machine Learning will go over the different automation scenarios and showcase how to implement them in your ML stack.
If you’re looking to accelerate your labeling without sacrificing the quality of your dataset, make sure to join!
Register to participate!
Pierre Leveau
Head of Machine Learning
Damien Mossuz
Product Manager
Do you have any specific questions about how to implement automations to label better and faster? Our speakers will be happy to answer all your questions during the webinar! Make sure to join!
"We have to spend a lot of time preparing high-quality data before we train the model. Just as a chef would spend a lot of time to source and prepare high-quality ingredients before they cook a meal, a lot of the emphasis of the work in AI should shift to systematic data preparation.“
Andrew Ng
Co-Founder @Google Brain
Founder @Coursera
"Even after 4 years I still haven't "solved" labeling workflows. Labeling, QA, final QA, auto-labeling, error-spotting, diversity massaging, labeling docs & versioning, ppl training, escalations, data cleaning, throughput & quality stats, etc."
Andrej Karpathy
Senior Director
@Tesla
“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.”
Edouard D'Archimbaud
Co-founder & CTO
@Kili Technology
Labeling Platform for High-quality Data
One tool to label, find and fix issues, simplify DataOps,
and dramatically accelerate the build of reliable AI
