How to Organize Data Labeling for Machine Learning: Approaches and Tools

 By KDnuggets - 2020-12-06

Description

The main challenge for a data science team is to decide who will be responsible for labeling, estimate how much time it will take, and what tools are better to use.

Summary

  • If there was a data science hall of fame, it would have a section dedicated to labeling.
  • Tasks like categorization of images of cars for computer vision projects, for instance, won’t be time-consuming and can be accomplished by a staff with ordinary — not arcane — knowledge.
  • Sometimes mistakes in annotations can happen due to a language barrier or a work division.
  • Outsourcing to companies Instead of hiring temporary employees or relying on a crowd, you can contact outsourcing companies specializing in training data preparation.

 

Topics

  1. Management (0.2)
  2. Backend (0.2)
  3. NLP (0.13)

Similar Articles

15 Essential Steps To Build Reliable Data Pipelines

By Medium - 2020-12-01

If I learned anything from working as a data engineer, it is that practically any data pipeline fails at some point. Broken connection, broken dependencies, data arriving too late, or some external…

Data Science Learning Roadmap for 2021

By freeCodeCamp.org - 2021-01-12

Although nothing really changes but the date, a new year fills everyone with the hope of starting things afresh. If you add in a bit of planning, some well-envisioned goals, and a learning roadmap, yo ...