Empower business users to extract insights with no-code, low-code solutions & generative AI
Machine learning can enable organizations of various industries and sizes to solve business challenges and achieve better outcomes. However, many struggle to implement ML effectively throughout the organization beyond their technical users. In this session, we showcase how you can use Amazon SageMaker Canvas to complete the ML lifecycle — from preparing data and creating models to generating predictions, without writing a single line of code. Find out how technical and non-technical users in your organization can utilize ready-to-use models or create your own to gain insights from your data and ML models with Amazon SageMaker Canvas. We then demonstrate how to easily access open-source and Amazon LLMs on Amazon SageMaker Canvas through a single interface. The session concludes with guidance on how you can build, deploy, and use a variety of ML models, including tabular, computer vision, and natural language processing without requiring deep machine learning knowledge.

Speaker: Tom Liu, Senior Technical Account Manager, AWS