My guest this time is Angie Hugeback, who is principal data scientist at Spare5. Spare5 helps customers generate the high-quality labeled training datasets that are so crucial to developing accurate machine learning models. In this show, Angie and I cover a ton of the real-world practicalities of generating training datasets. We talk through the challenges faced by folks that need to label training data, and how to develop a cohesive system for achieving performing the various labeling tasks you’re likely to encounter. We discuss some of the ways that bias can creep into your training data and how to avoid that. And we explore the some of the popular 3rd party options that companies look at for scaling training data production, and how they differ. Spare5 has graciously sponsored this episode; you can learn more about them at spare5.com. The notes for this show can be found at twimlai.com/talk/6.

Ask this episode

“What did the council decide on item 42?” — answered with the speaker and the moment.

Transcript

Related