The Challenges of Standardization in Data Science

This chapter discusses the contrasting viewpoints in standardization within data science, particularly in the context of machine learning models and workflows. It highlights the need for a standardized way to communicate with various machine learning libraries and test models across different types while expressing uncertainty regarding the direction of standardization in the field.