TESTING AND DEBUGGING MACHINE LEARNING MODELS

Debugging ML models is harder than debugging conventional programs. An ML codebase has a lot more moving elements than a typical codebase. There are datasets, fine-tuned model weights during training, optimization and its gradients changing during training, and so on. Monitoring and intervening during ML training is difficult. Because ML code is mostly based on higher-level frameworks that remove underlying complexities, models are difficult to debug.

Also known as: Testing and Debugging