In this episode of Talk Python To Me, Michael Kennedy interviews Catherine Nelson about transitioning data science projects from local notebooks to production workflows. Catherine shares her background, including her experience as a geologist turned data scientist, and discusses her book, "Software Engineering for Data Scientists." The conversation covers the benefits and drawbacks of using notebooks, strategies for refactoring notebook code into Python scripts, and the importance of testing. They also explore the role of AI in code generation and the challenges of maintaining machine learning models in production, emphasizing standardization and automation using frameworks like TensorFlow Extended and MLflow. Catherine offers advice for data scientists looking to improve their software engineering skills and encourages them to share their code and make it accessible to others.
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