SE Radio 641: Catherine Nelson on Machine Learning in Data Science
Software Engineering Radio - the podcast for professional software developers
Navigating Machine Learning Model Evaluation and Deployment
This chapter explores the critical distinctions between model analysis and data validation in machine learning. It emphasizes the evaluation of performance metrics, the necessity of bias testing, and the complexities of model interpretability and scaling during deployment. The discussion also highlights the evolving roles of AI engineers and data scientists, underscoring the collaborative efforts needed for successful integration of models into production environments.
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