5 QA Methods to Win the Race to Quality Data
The end result for every data labeling project is quality data - but how do you get there? There are several quality assurance workflow types but each has pros and cons when it comes to the quality and speed of data outputs. When you're evaluating data labeling providers or planning in-house processes, you should consider which QA workflow will work best for your business and data needs. In this panel discussion, CloudFactory experts explore: 5 QA workflows for data labeling teams Pros and cons, tools, and staffing needs for each workflow How each workflow impacts throughput and data quality Answers to audience questions during the Q&A portion
Session ID: Presentation Type: On-Demand Session (Recorded)
Date / Time: [Content On-Demand] @ On Demand ET (US)
Presented by:CloudFactory is a global leader in combining people and technology to provide a workforce in the cloud for machine learning and core business data processing. Click for more details and additional sessions and content.
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