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Dependency Inversion Principle for ML Engineers
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In the last video of the “SOLID for ML Engineers” series, you can learn about the Dependency Inversion Principle, , how to spot its violations, and how you can refactor ML code to respect it.
By satisfying the Dependency Inversion Principle, your ML code will protect your components from the most unstable elements of your code, decrease coupling, and facilitate testing.
Slides:
Code:
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Content:
0:00 Intro
0:17 Defining Dependency Inversion
0:57 How to spot DIP violations
1:30 Code example
2:56 DIP violations in the code example
3:46 Code example design
5:12 How to enforce DIP
6:20 Benefits of DIP
8:10 Refactoring the code
12:34 Final considerations
By satisfying the Dependency Inversion Principle, your ML code will protect your components from the most unstable elements of your code, decrease coupling, and facilitate testing.
Slides:
Code:
===============================
Interested in hiring me as a consultant/freelancer?
Join The Sound Of AI Slack community:
Connect with Valerio on Linkedin:
Follow Valerio on Facebook:
Follow Valerio on Twitter:
===============================
Content:
0:00 Intro
0:17 Defining Dependency Inversion
0:57 How to spot DIP violations
1:30 Code example
2:56 DIP violations in the code example
3:46 Code example design
5:12 How to enforce DIP
6:20 Benefits of DIP
8:10 Refactoring the code
12:34 Final considerations
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