Title

AWS re:Invent 2022 - Better decisions with no-code ML using SageMaker Canvas, feat. Samsung (AIM207)

Summary

• Shyam Srinivasan, a product manager for Amazon SageMaker Canvas, introduced the no-code ML service and its role in democratizing machine learning.
• SageMaker Canvas allows business analysts without ML expertise to build models and generate predictions using AutoML.
• Danny Smith provided a detailed demonstration of SageMaker Canvas, showcasing its ease of use and capabilities, including data import, model building, and predictions.
• Derek Lee from Samsung shared his team's experience with SageMaker Canvas, highlighting its impact on their demand forecasting and decision-making processes.
• The session emphasized the importance of no-code ML tools in enabling business users to leverage machine learning and the seamless collaboration between business teams and data science teams.
• Attendees were encouraged to explore SageMaker Canvas through workshops, a Coursera course, and the Canvas website, and to provide feedback for future improvements.

Insights

• The democratization of machine learning is a key theme, with tools like SageMaker Canvas making ML accessible to non-technical business users.
• No-code ML platforms are becoming increasingly important as they allow users to focus on business problems rather than the complexities of ML model building.
• The use of AutoML within SageMaker Canvas abstracts the complexities of model tuning and selection, making it easier for users to achieve accurate predictions.
• Real-world applications, such as Samsung's use case, demonstrate the practical benefits of no-code ML in improving business outcomes like demand forecasting.
• The session highlighted the growing trend of non-technical professionals building technology solutions, aligning with Gartner's prediction that 80% of technology products and services will be built by non-tech professionals by 2024.
• AWS is actively seeking customer feedback to continue improving SageMaker Canvas and other ML services, indicating a customer-centric approach to product development.