mFlow: Python Module for ML Experimentation Workflows

Introduces mFlow, a Python module crafted for structuring and executing machine learning experiments, particularly those dealing with multi-level data and leveraging parallel processing. It contrasts mFlow with the broader MLflow, highlighting their differing scopes in managing the machine learning lifecycle, where mFlow focuses on the experimentation workflow itself and MLflow offers end-to-end management. The documents outline mFlow's core features, such as modular workflow blocks and interoperability with scikit-learn and Spark, and provide practical examples of its implementation in areas like mobile health. While noting mFlow's strengths in specific experimental designs and data handling, the texts also touch upon its limitations compared to more comprehensive tools and its potentially smaller community.