Transparent Non-Executable Serialization of Machine Learning Models
An approach to exporting trained machine-learning models into a transparent, human-readable, non-executable format such as JSON, so that models can be safely inspected, verified, and shared without the code-execution risks of binary formats like pickle, and deserialized back into the exact original model. Students learn how a Chain-of-Responsibility network of type-specific transporters captures a model's structure, parameters, and custom components, and how wrapping asymmetric cryptography around the file adds publisher authentication.
PyMilo: A Python Library for ML I/O
PyMilo is an open-source Python package that addresses the limitations of existing Machine Learning (ML) model storage formats by providing a transparent, reliable, and safe method for exporting and …