Software engineering principles are frequently mentioned as a solution to data science's productivity problem. Unfortunately, rarely in a comprehensive format to be actionable or adopted for data-intensive use. In this talk, I will present a framework that enables practitioners to structure their projects and manage changes throughout the product lifecycle at low effort. Audience will also learn about a minimum set of programming concepts to make this a reality. The key takeaway for any Data Scientist is that you don't need to be a master programmer to start taking care of your own codebase. PUBLICATION PERMISSIONS:
PyData provided Coding Tech with the permission to republish PyData talks. CREDITS:
PyData YouTube channel: https://www.youtube.com/c/PyDataTV https://www.youtube.com/watch?v=zeubGVLH3Io