Agile Data Science
Sarah discusses the importance of integrating agile methodologies into data science, emphasizing the need for a seamless connection between model development and deployment. She highlights the role of automated machine learning in streamlining feature engineering and the significance of continuously monitoring model performance to quickly address any issues. The conversation sheds light on how a robust platform can empower data scientists to run experiments and iterate effectively.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Agile Data Science with Sarah Aerni - #143
Related Questions