Report Generation

Learn about report generation in the ML pipeline.

Each run of an ML pipeline must be associated with an export of training metrics. This is done so that data scientists can run multiple experiments and compare results.

Experiment tracking

Consider the following scenario: We’re doing a classification problem, and our baseline model has an accuracy of 92%. To try to improve the accuracy, we change a hyperparameter and train the model again. This time, we get an accuracy of 91%. Changing another ...