May 12, 2022, 6:07 p.m. | /u/ptrenko123

Data Science www.reddit.com

So everyone talks about weak supervision and how well it works for large-scale data labelling. I've always been a little confused about how the models would learn to avoid the labels which are actually wrongly labelled by the system. Would it not try to fit those data rows as well?

Whats the biggest challenge with implementing this setup?

ai datascience experience libraries product

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Data Management Associate

@ EcoVadis | Ebène, Mauritius

Senior Data Engineer

@ Telstra | Telstra ICC Bengaluru