According to recent studies, many machine learning workloads fail before they reach production. In this session, we invite you to hear our experience of successful machine learning projects. We will share the best practices in each phase of the machine learning lifecycle: scoping, data, modeling, and deployment. And we will demonstrate how AWS ML services can help you increase productivity, accelerate machine learning lifecycle and improve success rates.
29:27Amazon Fraud Detector is a fully managed service that enables customers to identify potentially fraudulent activities and eliminate online crime.
25:40As machine learning becomes mainstream, analysts are increasingly trying to apply it to their data to improve business outcomes.
26:00Learn how you can use AWS machine learning and AI services to address specific business outcomes.
32:32AI is key enabler of digital transformation & businesses must prepare for an AI-led future to solve real-world challenges. Learn how to democratise and build AI for your organisation at critical perfo
29:30Dayta.ai will share how their solution provides shopper analytics and analyses videos in real-time, Cyclops can connect most video cameras to acquire, evaluate and interpret in-store data.
30:28Sun Hung Kai Properties will showcase its current position in the machine learning development lifecycle, and how MLOps addresses operational challenges.