Refactoring A Data Science Project Part 3 - Configuration Cleanup

💡 Learn how to design great software in 7 steps: https://arjan.codes/designguide.

This is the final part of a 3-part miniseries in which I refactor a hand-written digit recognition data science project based on the MNIST dataset to improve the software design so it's easier to reuse and adapt. In this final part I cover grouping all configuration settings together in a single place and further cleanup of the main.py file and how data is being loaded.

Part 1: https://youtu.be/ka70COItN40
Part 2: https://youtu.be/Tx4AxbQNv3U
Part 3: https://youtu.be/8fFqakxhW84

Every Data Scientist Should Know This Design Principle (accompanying guest blog article @ AIgents): https://aigents.co/blog/publication/every-data-scientist-should-know-this-design-principle.

🎓 ArjanCodes Courses: https://www.arjancodes.com/courses/

🔖 Chapters:
0:00 Intro
1:08 Main.py cleanup
4:07 Configuration cleanup
5:57 Data loading cleanup
13:51 Looking back at what I did

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