Overview
Learn how to structure machine learning projects using the Clear Architecture framework to reduce technical debt and improve productivity in this 25-minute conference talk. Discover actionable software engineering principles tailored for data-intensive applications, and gain insights into essential programming concepts that enable effective project management. Explore techniques to maintain and organize your codebase with minimal effort, empowering data scientists to enhance their project structure throughout the lifecycle. Benefit from the speaker's diverse experience in fintech, mobile gaming, and quantitative research as he shares practical strategies for implementing clean architecture in data science projects.
Syllabus
Clean Architecture: How to Structure Your ML Projects to Reduce Technical Debt by Laszlo Sragner
Taught by
GAIA