There’s a fundamental problem with the typical ML model-development process: It evaluates models in terms of technical metrics like AUC, precision, or F-score, rather than business metrics like profit and savings – the stuff that actually matters to the company.

But this is beginning to change, as the industry broadens ML evaluation to also include ML valuation. Why? Because if you’re not measuring business value, you’re not pursuing business value. ML valuation provides the visibility needed to explicitly navigate ML model development toward monetary value. Critically, this move also helps to convince stakeholders. After all, business leaders don’t care about technical ML metrics. Instead, accessible business metrics and related visuals empower them to make informed decisions to authorize ML model operationalization.

In this session, Gooder AI CEO Eric Siegel will demonstrate a new category of software, ML valuation. The first such software solution, Gooder AI can valuate any ML model, effortlessly serving up an interactive visualization to navigate your ML projects and make the value easily understood by business stakeholders.