buckhx
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Hey HN, I'm curious how folks annotate their data to be used in ML pipelines (NLP/Vision) and what their experiences have been. Production/applied examples with teams of annotators would be great. From folks I've spoken…
- Unwinding Uber’s Most Efficient Service (2016) (medium.com)
- Unwinding Uber’s Most Efficient Service (2016) (medium.com)
- Unwinding Uber’s Most Efficient Service (2016) (medium.com)
- Unwinding Uber’s Most Efficient Service (2016) (medium.com)
- Unwinding Uber’s Most Efficient Service (2016) (medium.com)
- The Zagat Curator Program (curators.zagatlabs.com)
- The Zagat Curator Program (curators.zagatlabs.com)
- Botpress: The Wordpress of bots (botpress.io)
- 360 Interior Photos of the Infatuation's Best NYC Restaurants of 2016 (theinfatuation.com)
- Uber Restaurant Guide (uber.com)
- Unwinding Uber’s Most Efficient Service (medium.com)
- Unwinding Uber’s Most Efficient Service (medium.com)
- Unwinding Uber’s Most Efficient Service (medium.com)
- Unwinding Uber’s Most Efficient Service (medium.com)
- Unwinding Uber’s Most Efficient Service (medium.com)
- Unwinding Uber's Most Efficient Service (in Go) (github.com)
- Unwinding Uber’s Most Efficient Service (medium.com)
- Unwinding Uber’s Most Efficient Service (medium.com)
- Unwinding Uber’s Most Efficient Service (medium.com)