Is Poorly Labelled Data the Culprit for Failed AI Projects?

Abstract: 

In this talk we will examine the key phases on AI solution development and the critical aspects of humans in the loop (HITL) to ensure their success. From data cleansing to annotation to quality control, HITL has been shown to improve ML/AI project quality, while improving efficiency and accelerating time to value across multiple industries, including finance, retail, agriculture and more. We will share how the right combination of people and technology can be effectively paired with insight from an experienced CloudFactory tooling partner, and share an actual use case of this having been applied to a recent medical AI project.

Bio: 

Andy has 20+ years experience in customer success, consulting, training & coaching for martech, edtech and AI businesses. Commercially focussed & high achiever in client retention, expansion & satisfaction metrics. Builder & leader of high performing CS teams, mentor and advisor on strategic growth tactics. Customer experience first attitude to products, services and interactions. Creative & entrepreneurial with a passion for serving others. Driven to deliver for customers, stakeholders and execs with a consistent focus on providing value.

Open Data Science

 

 

 

Open Data Science
One Broadway
Cambridge, MA 02142
info@odsc.com

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