Overview
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Explore software development techniques tailored for Machine Learning and Data Science in Python through this insightful PyCon US talk. Discover how to create code that facilitates fast exploration, enables efficient checkpoints and optimizations, implements declarative queries and functions, and provides abstraction for production tracking and monitoring. Learn general guidelines for approaching ML development from a software engineering perspective, including defining entities, determining appropriate abstraction levels, and avoiding common design pitfalls. Apply these principles to a concise end-to-end problem, gaining practical insights for enhancing your ML development workflow. Access accompanying slides for a comprehensive understanding of the concepts presented in this 37-minute talk by Pablo Alcain.
Syllabus
Talk - Pablo Alcain: Software Development for Machine Learning in Python
Taught by
PyCon US