Improving Productivity for Building ML Workloads Using Amazon SageMaker Autopilot

Learn how to automatically train and tune the best machine learning models using Amazon SageMaker Autopilot in this 19-minute conference talk from the Toronto Machine Learning Series. Explore a Customer Churn use case to understand how to maintain full control and visibility while automating the model training process. Discover techniques for deploying models to production and iterating on recommended solutions using Amazon SageMaker Studio to enhance model quality. Gain insights into streamlining each step of the machine learning process, making it easier to develop high-quality models and improve productivity for building ML workloads.

How to improve productivity for building ML workloads using Amazon SageMaker Autopilot