What role do ML Logs serve within the AI Center?

ML Logs are crucial in the AI Center as they track the starting and progression of machine learning packages. This tracking allows users to monitor the lifecycle of their machine learning models, ensuring that progress can be evaluated effectively. By maintaining logs throughout the training and deployment processes, it becomes possible to analyze the performance of different models, understand training durations, and identify any issues that may arise during these processes.

The focus on logging the progression provides insights into how well a model is performing over time and enables data scientists and engineers to make informed decisions based on comprehensive data. This continuous monitoring also supports troubleshooting and optimization, which are essential in machine learning workflows.