MLaaS also facilitates clear knowledge documentation. The following types of data are captured by Uber’s Michelangelo88: Who trained the model Start and end time of the training job (some complicated training jobs can take hours or even days) Full model configuration (features used, hyper-parameter values, etc.) Reference to training and test datasets Model accuracy metrics Standard charts and graphs for each model type Full learned parameters for the model Summary statistics for model visualization Other notes and information
