Satadal Bhattacharjee

Health data is frequently incomplete and inconsistent. It is often unstructured, with information contained in clinical notes, laboratory reports, insurance claims, medical images, and recorded conversations across disparate formats and systems.

During ML model training, it’s challenging to ensure that models are progressively learning the correct values for different parameters and to analyze and debug model characteristics without building additional tools, making the process time-consuming and cumbersome. Come learn about Amazon SageMaker Debugger, a new capability that provides complete insights into the training process by...