Overview
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Explore the parallels between software development in 1999 and current data science and AI practices in this conference talk from GOTO Copenhagen 2018. Discover how the lack of appropriate tooling, CI/CD pipelines, and model health monitoring impacts productivity and reproducibility in the field. Learn about the challenges of collaboration, governance, and compliance in data science teams. Gain insights into proposed solutions, including an architecture and open-source tools, to address these issues. Compare the evolution of software development and DevOps with that of data science and AI to understand the potential for improvement in productivity and reproducibility.
Syllabus
Inextricably Linked: Reproducibility & Productivity in Data Science & AI • Mark Coleman • GOTO 2018
Taught by
GOTO Conferences