Wait Time Prediction Using Amazon SageMaker Canvas - A CATCHTABLE Case Study

Learn from a Korean-language lightning talk how CATCHTABLE, Korea's premier dining reservation platform, implemented wait time prediction capabilities using AWS's ensemble methods. Explore their journey of building an efficient data pipeline with Amazon SageMaker Canvas, covering data preparation, model creation, and production deployment processes. Discover how to develop machine learning models through a no-code approach, customize code for specific needs, and leverage natural language-based querying to streamline preprocessing tasks and reduce development time.