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Ananda Jana, Program Manager, Sasken | LinkedIn

The accuracy of data annotation plays a crucial role in the successful and scalable deployment of machine learning activity. However, annotation is a monotonous manual job prone to errors, which needs a framework to ensure adherence to quality goals, controllability, and the alignment of control limits within specification limits.

In this free webinar, Sasken’s Ananda Jana presents a structured approach to achieving quality assurance in data annotation.

Key topics and takeaways:

  • Learn about accuracy expectation levels from real-life data annotation projects
  • Discover approaches for in-process quality monitoring
  • Understand the factors that impact accuracy
  • Learn how to improve data annotation accuracy to meet specification limits

Webinar video

Webinar slides

Meet the experts

Ananda Jana

Program Manager, Sasken