A Flexible Cell Classification for ML Projects in Jupyter Notebooks

arXiv:2403.07562v1 Announce Type: cross
Abstract: Jupyter Notebook is an interactive development environment commonly used for rapid experimentation of machine learning (ML) solutions. Describing the ML activities performed along code cells improves the readability and understanding of Notebooks. Manual annotation of code cells is time-consuming and error-prone. Therefore, tools have been developed that classify the cells of a notebook concerning the ML activity performed in them. However, the current tools are not flexible, as they work based on look-up tables that …

abstract annotation arxiv cells classification code cs.lg cs.se development environment error experimentation interactive jupyter jupyter notebooks machine machine learning ml projects notebook notebooks projects readability solutions tools type understanding