In this ebook, Sama answers data labeling FAQs such as “How much data do I need?”, “Which parts of my data should I annotate first?” and many more.
Not all retailers have the resources or know-how to effectively turn the data they have into a competitive edge. As ML models for common retail use cases become increasingly “off the shelf,” the real competitive advantage is increasingly going to lie with your data and what you do with it. Data and annotations are equally important at every stage of the AI model lifecycle, whether you’re training your model, testing it, or monitoring it in production.As you progress through the AI model lifecycle, it’s likely that you’ll ask some of the following questions (and if you aren’t, then you probably should be):
At Sama, we’ve helped hundreds of retailers answer these data labeling questions and more. We’ve compiled our advice in this ebook, along with recommendations for approaching your data annotation strategy holistically and sustainably.