Roles in Machine Learning Workflows

This chapter explores the distinct roles of data scientists and machine learning engineers within machine learning workflows, detailing their responsibilities from problem validation to model deployment. It highlights the challenges faced in smaller companies where team members often wear multiple hats due to resource limitations and underlines the importance of software engineering principles for data scientists. Furthermore, the discussion emphasizes data ingestion, validation, and the critical nature of collaboration and automation in ensuring effective machine learning pipelines.