AWS Summit Online Hong Kong 2022 - AI & Machine Learning

  • Identifying fraud in the digital era with Amazon Fraud Detector29:27

    Identifying fraud in the digital era with Amazon Fraud Detector

    Amazon Fraud Detector is a fully managed service that enables customers to identify potentially fraudulent activities and eliminate online crime.

    Watch Video
  • Accelerate innovation using Low-Code & No-Code ML25:40

    Accelerate innovation using Low-Code & No-Code ML

    As machine learning becomes mainstream, analysts are increasingly trying to apply it to their data to improve business outcomes.

    Watch Video
  • Improving business efficiency with AI/ML26:00

    Improving business efficiency with AI/ML

    Learn how you can use AWS machine learning and AI services to address specific business outcomes.

    Watch Video
  • Sponsored by Intel: Solving business challenges with AI powered by Intel on AWS32:32

    Sponsored by Intel: Solving business challenges with AI powered by Intel on AWS

    AI 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

    Watch Video
  • Transforming traditional stores with Machine Learning (featuring Dayta.ai)29:30

    Transforming traditional stores with Machine Learning (featuring Dayta.ai)

    Dayta.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.

    Watch Video
  • Automate your Machine Learning lifecyle with MLOps (featuring Sun Hung Kai Properties)30:28

    Automate your Machine Learning lifecyle with MLOps (featuring Sun Hung Kai Properties)

    Sun Hung Kai Properties will showcase its current position in the machine learning development lifecycle, and how MLOps addresses operational challenges.

    Watch Video
  • How to succeed in a Machine Learning project25:55

    How to succeed in a Machine Learning project

    We will share the best practices in each phase of the machine learning lifecycle: scoping, data, modeling, and deployment.

    Watch Video
  • loading
    Loading More...