Continuous Delivery for Machine Learning - Patterns and Pains

Explore the challenges and solutions of implementing Continuous Delivery (CD) for machine learning and data-driven systems in this 44-minute conference talk by Emily Gorcenski at NDC Conferences. Delve into the complexities of achieving CD in data systems, comparing it to traditional software contexts. Examine common pain points encountered in the process and discover effective patterns used to address these challenges. Gain valuable insights from Gorcenski's extensive experience in developing CD practices, and learn how to navigate the evolving demands and complex data architectures inherent in machine learning projects. Enhance your understanding of CD implementation strategies specifically tailored for data-centric environments.